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About The RoleTaktile is redefining how financial institutions use AI to make critical decisions, and we're growing fast. As a Lead Forward Deployed Engineer, you'll be at the heart of that transformation, owning the technical journey from customer onboarding to production-grade AI deployments that deliver real business impact.If you're passionate about tech and AI, stay up to date on the latest AI developments, and have extensive experience with Python, SQL, REST APIs, you'll thrive here.What You'll Do as Lead Forward Deployed EngineerLead complex AI-driven Taktile deployments in production. You own technical delivery across multiple deployments, from scoping high-impact Agentic AI use cases to stable production.Apply your technical expertise, problem-solving skills and creativity to help organizations address real-world challenges. Your day could include designing solution architectures, developing decision logic and deploying production-grade Generative AI agents, or aligning with key customer stakeholders - all while ensuring an outstanding experience and rapid time to value for Taktile’s customers.You effectively scope work, sequence delivery, and proactively remove blockers, while making thoughtful trade-offs between scope, speed, and quality to ensure successful and timely project delivery.Partner with Taktile’s product management team to turn your understanding of customer needs into actionable product insights, directly influencing the evolution of Taktile’s product roadmap.Develop reusable resources, best practices, and tools to share your expertise and help scale the forward deployed engineering function across the organization.You actively coach and mentor junior Forward Deployed Engineers, supporting their development and success.About YouYou bring 6+ years of engineering or technical deployment experience that includes customer-facing work.You have strong technical background, preferred in fields such as Computer Science, Mathematics, Software Engineering, Physics, and Data Science.You write and review production-grade Python and SQL, and have strong command of REST API design and integrations.You excel at breaking down complex problems and making quick, well-informed decisions even under pressure.You build strong relationships with both technical and business stakeholders at all levels, driven by curiosity and a customer-centric mindset that helps you understand their needs and solve their challenges.You're collaborative, curious, and low-ego- you work well across product, engineering, and GTM teams, and you bring a genuine desire to understand customers' businesses.You are open to a hybrid work model and can work from our Berlin or London office at least three days per week.Ideal Qualifications (but not required)You have 6+ years of experience as a Forward Deployed Engineer, Solution Engineer, Implementation Specialist or an equivalent position within a B2B SaaS company.You have experience in building AI applications within financial servicesYou have experience in applying and optimizing statistical and machine learning models to solve business problems.You have experience with at least one of the major cloud platforms (AWS, Azure, GCP).What We OfferWork with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields. If you are similarly capable, caring, and driven, you'll find yourself at home here.Make an impact and meaningfully shape an early-stage company.Experience a truly flat hierarchy and communicate directly with founding team members. Having an opinion and voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo.Learn from experienced mentors and achieve tremendous personal and professional growth. Get to know and leverage our network of leading tech investors and advisors around the globe.Receive a top-of-market equity and cash compensation package.Get access to a self-development budget you can use to e.g. attend conferences, buy books or take classes.Use the equipment of your choice including meaningful home office set-up.Our StanceWe're eager to meet talented and driven candidates regardless of whether they tick all the boxes. We're looking for someone who will add to our culture, not just fit within it. We strongly encourage individuals from groups traditionally underestimated and underrepresented in tech to apply.We seek to actively recognize and combat racism, sexism, ableism and ageism. We embrace and support all gender identities and expressions, and celebrate love in its many forms. We won't inquire about how you identify or if you've experienced discrimination, but if you want to tell your story, we are all ears.About UsTaktile helps financial institutions make smarter, safer decisions with the power of AI. Our software gives teams the tools to automate complex decisions — like who to onboard, how to underwrite, or when to flag suspicious activity — with full visibility and control.By combining AI with a rich ecosystem of financial data, Taktile enables companies to adapt their decision-making in real time as markets, customer behavior, and risks evolve.Our mission is to build the world’s leading platform for automated decision-making in financial services — setting the standard for how AI is applied responsibly and effectively in this industry.We were founded by machine learning and data science experts with deep experience in financial services. Today, our team works across Berlin, London, and New York, bringing together engineers, entrepreneurs, and researchers from companies like Google, Amazon, and Meta, as well as fast-growing startups and enterprise leaders.Backed by top investors including Y Combinator, Index Ventures, Balderton Capital, and Tiger Global, along with the founders of Looker, GitHub, Mulesoft, Datadog, and UiPath - we’re building a world-class organization across all functions and levels to power the next generation of AI-driven decision-making in financial services.

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.About the RoleAs a GNC Engineer on the UAV team, you’ll design and develop advanced guidance, navigation, and control (GNC) solutions. From integrating and fusing sensor data to developing control laws and flight trajectories, you'll take your work from simulation to embedded implementation—and ultimately to live flight testing.ResponsibilitiesDevelop state-of-the-art navigation and sensor fusion algorithms for UAVsDesign and implement GNC and flight control systemsBuild filtering and estimation strategies for robust and efficient flight performanceRun extensive simulations (Monte Carlo, SITL, HITL) and coverage testingAnalyze test flight data and refine algorithmic performanceSupport full-stack system integration: GNSS, INS/IMU, localization, and fusionMaintain and evolve a flight-proven flight computer across multiple UAV platformsRequirementsEducation : Engineering school or master's degree in computer science, engineering, or a related technical field3+ years of experience in aerospace GNC systemsStrong foundations in control theory, estimation, and sensor integrationProficient in Python and embedded C/C++Experience with simulation tools (e.g., Gazebo) and version control (Git)Familiarity with open-source autopilots (PX4, Ardupilot, Betaflight, etc.)Hands-on electronics and integration skills: debugging, soldering, harnessingBonus: FPV pilot hobbyistWe look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About the Role The Turbo team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale. Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design. You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal. Requirements We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay. You might be a good fit if you: Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others: Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving. RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models. Model architecture design for Transformers or other large neural nets. Distributed systems / high‑performance computing for ML. Are comfortable working from algorithms to engines: Strong coding ability in Python Experience profiling and optimizing performance across GPU, networking, and memory layers. Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack. Have a solid research foundation in your area(s) of depth: Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems). Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API). Operate well as a full‑stack problem solver: You naturally ask: “Where in the stack is this really bottlenecked?” You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins. Minimum qualifications 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source). Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience. Demonstrated experience owning complex technical projects end‑to‑end. If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement. Responsibilities Advance inference efficiency end‑to‑end Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference. Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc. Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost. Unify inference with RL / post‑training Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems. Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper. Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack. Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers. Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design. Own critical systems at production scale Profile, debug, and optimize inference and post‑training services under real production workloads. Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed. Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously. Provide technical leadership (Staff level) Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training. Mentor other engineers and researchers on full‑stack ML systems work and performance engineering. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy    

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Zoox is on a mission to reimagine transportation and build autonomous robotaxis from the ground up that are safe, reliable, clean, and enjoyable for everyone. With bidirectional driving capabilities and four-wheel steering, our vehicle allows us to maneuver through compact spaces and change directions without needing to reverse. We are still in the early stages of deploying our robotaxis, and it is a great time to join Zoox and have a significant impact on executing this mission.  Our growing Software Infrastructure engineering leadership team is looking for a Senior Engineering Manager, ML Platform. The centralized ML Platform team at Zoox plays a crucial role in enabling innovations across all our Autonomy and Data Science teams to develop and deploy models across our robotaxi and cloud infrastructure, and to work on cutting-edge training and inference optimization techniques. The OpportunityWe are working on many interesting challenges to enable rapid experimentation and scale our multi-modal Foundation models and RL infrastructure, and ensure these models run efficiently on our vehicles, meeting our latency targets. You will get to work across all ML teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and our Advanced Hardware Engineering group, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, deep learning frameworks, and inference libraries used by our applied research teams for in- and off-vehicle ML use cases. You will lead a team of strong software engineers and managers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent.In this role, you will:Vision: Develop and execute a strategic vision for our ML training platform, ensuring scalability, reliability, and performance to support large-scale Foundation and RL models.Technical acumen: Lead the design, implementation, and operation of a robust and efficient ML training platform to enable the training, experimentation, validation, and monitoring of ML models.Hiring: Attract, hire, and inspire a diverse world-class engineering team, fostering a culture of innovation, collaboration, and excellence.Partnership: Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers to define requirements and align on architectural decisions.Mentorship: Enable the engineers in the team to grow their careers by providing the right opportunities along with clear and timely feedback.Qualifications10+ years of relevant experience, including 4+ years of management experience managing other managers and engineers.Experience building user-friendly ML Infrastructure that enabled large-scale model training and high-throughput, low-latency serving use cases.Experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs for distributed model training.Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks. 317,000 - 370,000 a yearBase Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

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About UsAt Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.About the Team the Platform TeamThe Platform team serves as the foundational layer that keeps Hayden's operations running reliably and at scale. This team is responsible for ensuring that Perception algorithms run smoothly across both purpose-built edge hardware and public cloud infrastructure. The team manages event processing, starting from device and ending at delivery to partners. It is also responsible for the fleet's health. Security, compliance, data governance, and data privacy is also within the responsibility of the Platform team.About the RoleAs a Platform Engineering Intern at Hayden AI, you’ll work on the foundational systems that power our entire product. This is not a sandbox role, you will contribute directly to the infrastructure, services, and data pipelines that ensure our Perception algorithms run reliably across edge devices and cloud environments.You will partner closely with senior engineers to build and improve the systems that move data from devices in the field all the way through event processing and delivery to our partners. Your work may touch cloud services, backend systems, fleet health monitoring, data tooling, or internal platforms that support security, compliance, and governance.This role is ideal for someone who wants to understand how large-scale AI systems operate in production—from edge hardware to cloud infrastructure—and is excited by reliability, performance, and scalability challenges.You will gain hands-on experience designing, building, testing, and deploying production-grade systems while learning how high-performing infrastructure teams operate.This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.Key ResponsibilitiesBelow are your primary responsibilities. These represent the core areas where you’ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.Take ownership of a real project and see it through to completionBuild and ship features with support from senior engineersWrite clean, scalable codeTest your work and iterate quicklyBe involved in everything from design discussions to deploymentCollaborate with engineers in code reviews and team discussionsParticipate in standups, sprint planning, and retrospectivesSupport the team on ad hoc engineering tasks as they come upHelp improve performance, reliability, or usability where needed​​Ask questions, seek feedback, and apply it quicklyDeliverables or project examples:GPS data analysisTrain Deep learning modelCreate AI datasetsLidar/Camera data toolingTest cases for end-to-end system performanceDevelop a cloud service in the event processing pipelineAdd page or a new user flow to the Portal web applicationRequired QualificationsThe qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.Education:Currently in your final year of a Bachelor’s program, or enrolled in a Master’s or PhD program in Computer Science. Technical Experience:Experience in one or more of the following programming languages:Go, PythonPersonal Attributes:Detail-oriented with a high bar for quality and accuracy.Curious and self-driven, motivated to dig into problems and find root causes.Strong communicator who can clearly document findings and surface issues to the right stakeholders.Collaborative team player who thrives in cross-functional environments.Organized and reliable, with the ability to manage multiple tasks and follow through consistently.Comfortable with ambiguity and able to make progress with limited direction.

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About the roleAs an Android Developer at Flowith, you'll be at the forefront of mobile innovation, designing and developing cutting-edge Android applications that integrate advanced AI capabilities. This role combines technical expertise with creative collaboration through our unique Vibe Coding approach, where 70-99% of your time will be dedicated to collaborative programming in a creative, dynamic environment. You'll transform complex requirements into intuitive user experiences while exploring the latest Android technologies to power our innovative products.Responsibilities:Design and develop the flowith's Android platform products Implement and optimize AI features for mobile applicationsCollaborate with product, design, and backend teams to create exceptional user experiencesExplore and implement cutting-edge Android technologies and frameworks Conduct code reviews and performance optimizationsParticipate in team Vibe Coding sessions, working collaboratively in a creative atmosphere工作内容：核心产品开发：主导 Flowith 安卓平台产品的架构设计与核心开发，从底层保障 APP 的极致性能。沉浸式 Vibe Coding：将 70%-99% 的时间投入到充满创意的结对与协作编程中，将灵感转化为代码。AI 能力移动端化：在手机端深度集成、落地并持续优化 AI 核心功能，让复杂的前沿模型在移动设备上跑得又快又稳。跨界体验打磨：与产品、设计及后端研发团队无缝咬合，跨越技术与业务的边界，共同打磨出令人惊艳的用户体验。前沿技术破圈与护航：持续探索并引入最前沿的安卓技术与框架；把控代码质量，主导 Code Review 与深度的性能调优。RequirementsDemonstrated experience building and shipping applications, websites, or hardware projects for personal interest or commercial purposesProficiency in Java/Kotlin with strong knowledge of Android development frameworks and ecosystemSolid understanding of UI design principles, particularly Material Design Familiarity with mobile AI technologies implementation (e.g., TensorFlow Lite)Strong programming fundamentals, clean coding practices, and excellent problem-solving abilitiesAbility to thrive in the Vibe Coding environment, enjoying collaborative creative programmingWorking knowledge of English; preference given to candidates with open-source project experience实战创作者：有过真正主导并打包上线的应用、网站或硬件项目经验—无论这是出于商业目的，还是纯粹的个人狂热与兴趣。安卓原生极客：精通 Java/Kotlin，深入理解 Android 开发框架与技术生态。具备扎实的编程底子、Clean Code（整洁代码）的强迫症，以及绝佳的问题解决能力。端侧 AI 玩家：熟悉并在意移动端 AI 技术的落地实现（如 TensorFlow Lite 等），渴望探索端侧智能的性能边界。审美在线的工程师：扎实掌握 UI 设计原则（尤其是 Material Design），不仅懂代码，更懂交互，对移动端产品的美感有自己的坚持。Vibe Coding 狂热分子：极度适应并享受Vibe Coding，能在高度动态的环境中与团队同频共振。加分项：具备良好的英文工作沟通能力；有活跃的 Open-source（开源）项目贡献经验是巨大的加分项。BenefitsWorkspace, Culture & LifestyleAwesome Teammates: Work alongside a kind, creative, and hardworking crew of occasional "geeks" and visionaries.Building the AGI Future: Participate in the in-house development of rapidly evolving AI agents and explore the future of AGI interactive interfaces.Cool Offices in SH & SF: Enjoy our ultra-open workspaces with the ultimate freedom to seamlessly switch between our Shanghai and San Francisco locations.Pet-Friendly Workplace: Bring your furry friends to work! Come play with our resident Orange Tabby and Golden Retriever Mix, or bring your own pets to hang out.Island Hackathons: Join our annual internal hackathons, where we select a new city or country each year for innovative coding sessions and team bonding.Free AI Tools & Tech Gear: Enjoy free, unlimited access to cutting-edge AI tools, plus the latest tech equipment like Apple Vision Pro and FPV drones.Tech Events: Regularly participate in top-tier global tech meetups and innovation showcases.Parties & Events: Celebrate with monthly birthday bashes and annual milestone partiesFree Snacks & Drinks: Stay fueled with an endless supply of your favorite beverages and unlimited complimentary snacks.Work ArrangementsFlexible Working Hours: Customize your schedule by arriving at the office between 10 AM and 1 PM for a standard 8-hour workday, 5 days a week.Remote Work & Care: Embrace a supportive hybrid work model, featuring 1 additional Work-From-Home (WFH) day per month exclusively for female employees.Comprehensive Benefits PackageCompetitive Compensation: Earn an above-market salary structure with an optional equity/stock options package.Wellness Program: Take care of your body and mind with free gym access and monthly on-site professional massages.Exclusive Swag & Perks: Receive holiday surprise gift boxes, premium custom company apparel (T-shirts, hoodies, and jackets), and occasional exclusive internal brand discounts.

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Role Overview Scale’s rapidly growing International Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.About the role We are looking for a senior-level Offensive Security Engineer to serve as a high-impact "adversary-in-residence" for Replit’s cloud-native platform. At Replit, security isn't just about perimeter defense; it’s about the integrity of the code that powers millions of environments.In this role, you will lead advanced "whitebox" penetration testing engagements—diving deep into our source code to identify systemic weaknesses, logic flaws, and architectural gaps. You will simulate sophisticated adversary tactics across our web applications, APIs, and containerized infrastructure, ensuring that our AI-integrated development environment remains the most secure place for the world’s software to live. What You'll DoLead Whitebox Penetration Testing: Execute end-to-end testing with full access to source code. You will perform manual code-level inspections to uncover complex logic flaws and authorization bypasses that automated tools miss.Simulate Adversarial Attacks: Conduct Red and Purple team engagements across our cloud-native stack (K8s, Docker), simulating how a sophisticated actor might move from a code-level exploit to infrastructure-wide impact.Secure AI-Enabled Systems: Perform offensive testing on LLM-backed applications and agentic AI workflows, focusing on prompt injection, data leakage, and abuse of AI-driven components.Vulnerability Research & Chaining: Identify, exploit, and demonstrate realistic business risk by chaining vulnerabilities—from the application layer down through our internal trust boundaries.Build Offensive Tooling: Contribute to internal security frameworks and build AI-assisted testing tools to automate the discovery of common bug classes while maintaining deep manual testing depth.Partner with Engineering: Work closely with product teams and security architects to explain root causes, influence design guardrails, and triage high-priority findings from our Bug Bounty (HackerOne) program.Required Skills & ExperienceExperience: 7+ years of hands-on experience in penetration testing, offensive security, or vulnerability research.Code Fluency: You are a practitioner of whitebox testing. You can navigate large codebases and have a deep understanding of modern application architectures and secure coding pitfalls.Cloud-Native Context: You are comfortable in a cloud-native environment. While your focus is the code, you understand how it interacts with Kubernetes, Docker, and hybrid cloud infrastructure.Engineering Skills: Strong proficiency in Go, Python, or TypeScript. You should be capable of writing custom scripts, payloads, and proof-of-concept exploits.Adversarial Mindset: You enjoy the "hunt" and have a proven track record of manual exploitation beyond automated scanners.Communicator: You can translate a complex code-level exploit into a clear narrative that helps engineering teams understand risk and prioritize fixes.Bonus QualificationsPublic recognition on platforms like HackerOne or Bugcrowd.Experience building or extending AI-based security testing tools.Background in incident response or detection engineering from the defensive side.Published CVEs or security research in the cloud-native or AI space.This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday. Full-Time Employee Benefits Include:💰 Competitive Salary & Equity💹 401(k) Program with a 4% match⚕️ Health, Dental, Vision and Life Insurance🩼 Short Term and Long Term Disability🚼 Paid Parental, Medical, Caregiver Leave🚗 Commuter Benefits📱 Monthly Wellness Stipend🧑‍💻 Autonomous Work Environment🖥 In Office Set-Up Reimbursement🏝 Flexible Time Off (FTO) + Holidays🚀 Quarterly Team Gatherings☕ In Office AmenitiesWant to learn more about what we are up to?Meet the Replit AgentReplit: Make an app for thatReplit BlogAmjad TED TalkInterviewing + Culture at ReplitOperating PrinciplesReasons not to work at ReplitTo achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

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About the Role The Turbo team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale. Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design. You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal. Requirements We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay. You might be a good fit if you: Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others: Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving. RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models. Model architecture design for Transformers or other large neural nets. Distributed systems / high‑performance computing for ML. Are comfortable working from algorithms to engines: Strong coding ability in Python Experience profiling and optimizing performance across GPU, networking, and memory layers. Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack. Have a solid research foundation in your area(s) of depth: Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems). Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API). Operate well as a full‑stack problem solver: You naturally ask: “Where in the stack is this really bottlenecked?” You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins. Minimum qualifications 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source). Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience. Demonstrated experience owning complex technical projects end‑to‑end. If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement. Responsibilities Advance inference efficiency end‑to‑end Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference. Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc. Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost. Unify inference with RL / post‑training Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems. Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper. Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack. Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers. Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design. Own critical systems at production scale Profile, debug, and optimize inference and post‑training services under real production workloads. Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed. Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously. Provide technical leadership (Staff level) Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training. Mentor other engineers and researchers on full‑stack ML systems work and performance engineering. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy    

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About the teamThe Safety Systems org ensures that OpenAI’s most capable models can be responsibly developed and deployed. We build evaluations, safeguards, and safety frameworks that help our models behave as intended in real-world settings.The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework.Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.The mission of the Preparedness team is to:Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards risks whose impact could be catastrophicEnsure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systemsPreparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.About the roleAs frontier AI systems become more capable, they are increasingly able to pursue long-horizon goals, use tools, adapt to feedback, and operate with greater autonomy. These advances create enormous potential benefits, but they also introduce the risk that models may behave in ways that are misaligned, deceptive, or difficult to supervise or contain. Reducing loss of control risk is therefore a core challenge for safely developing and deploying advanced AI systems.As a Researcher for loss of control mitigations, you will help design and implement an end-to-end mitigation stack to reduce the risk of intentionally subversive or insufficiently controllable model behavior across OpenAI’s products and internal deployments. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as model capabilities, deployment patterns, and threat models evolve.In this role, you will:Design and implement mitigation components for loss of control risk—spanning prevention, monitoring, detection, containment, and enforcement—under the guidance of senior technical and risk leadership.Integrate safeguards across product and research surfaces in partnership with product, engineering, and research teams, helping ensure protections are consistent, low-latency, and resilient as usage and model autonomy increase.Evaluate technical trade-offs within the loss of control domain (coverage, robustness, latency, model utility, and operational complexity) and propose pragmatic, testable solutions.Collaborate closely with risk modeling, evaluations, and policy partners to align mitigation design with anticipated failure modes and high-severity threat scenarios, including deceptive alignment, hidden subgoals, reward hacking, and attempts to evade oversight.Execute rigorous testing and red-teaming workflows, helping stress-test the mitigation stack against increasingly capable and potentially subversive model behaviors—such as sandbagging, monitor evasion, exploit-seeking, unsafe tool use, or strategic deception—and iterate based on findings.You might thrive in this role if you:Have a passion for AI safety and are motivated to make cutting-edge AI models safer for real-world use.Bring demonstrated experience in deep learning and transformer models.Are proficient with frameworks such as PyTorch or TensorFlow.Possess a strong foundation in data structures, algorithms, and software engineering principles.Are familiar with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization.Excel at working collaboratively with cross-functional teams across research, policy, product, and engineering.Have significant experience designing and evaluating technical safeguards, control mechanisms, or monitoring systems for advanced AI behavior.(Nice to have) Bring background knowledge in alignment, control, interpretability, robustness, adversarial ML, or related fields.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Our MissionReflection’s mission is to build open superintelligence and make it accessible to all.We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.The Roles MissionBridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models — from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines.Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility.What This Team DoesThis team owns and evolves the core infrastructure behind our training systems.We focus on:Reinforcement learning training infrastructureDistributed training and inference systemsExperiment infrastructure and reproducibilityLarge-scale data pipelinesThe goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale.About the RoleYou will architect and optimize the core training infrastructure that powers our models. This includes RL training loops, distributed GPU systems, and large-scale data pipelines.You will work closely with researchers to transform new ideas into reliable, scalable training systems.Responsibilities include:Designing and optimizing large-scale training loops and data pipelines.Implementing state-of-the-art techniques and ensuring they are numerically stable and computationally efficient.Building internal tooling for launching, monitoring, and reproducing complex experiments.Diagnosing deep bottlenecks across the training stack (GPU memory issues, communication overhead, dataloader stalls).Translating research prototypes into reusable, production-grade infrastructure.What You'll Work WithRL SystemsPPO / GRPO style training loopsRLHF / RLAIF style pipelinesRollout generation and reward modelingOnline learning and evaluation systemsDistributed TrainingGPU parallelism (data, tensor, pipeline, expert)Large-scale distributed training infrastructureCommunication optimization (NCCL, RDMA, GPU interconnects)FSDP / ZeRO and model shardingOrchestration & Runtime SystemsRay, Kubernetes, SlurmDistributed runtimes and async systemsContainerization and sandboxingFrameworksPyTorchJAXMegatron-style training stacksTriton / custom kernelsData InfrastructureLarge-scale dataset curation pipelinesDeduplication and filtering systemsTokenization and preprocessingDistributed data processing frameworksAbout YouYou are a strong software engineer who speaks the language of machine learning.You may not have a PhD, but you know how to implement a research paper.You have deep experience in at least one of the following: Reinforcement Learning Systems, Distributed Training & Inference or Data InfrastructureYou enjoy working at the boundary between:Machine learning algorithmsDistributed systemsHigh-performance computingYou care deeply about performance, numerical stability, and reproducibility.You thrive in high-agency environments and enjoy solving hard technical problems.What We Offer:We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models.We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time. Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.

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Join the Sleep Fitness MovementAt Eight Sleep, we’re on a mission to fuel human potential through optimal sleep. As the world’s first sleep fitness company, we’re redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data-driven recovery experience. We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide. Recognized as one of Fast Company's Most Innovative Companies in 2019, 2022, and 2023, and twice named to TIME's “Best Inventions of the Year.” We operate like a high-performance team: fast, focused, and motivated by impact. We don’t just ship; we iterate, refine, and obsess over the details that help our members sleep better and wake up stronger. Every role at Eight Sleep is a chance to create cutting-edge technology, collaborate with world-class talent, and help shape a future where sleep isn’t passive - it’s a powerful tool for living better. If you’re tired of the ordinary and driven to build at the edge of what’s possible, this is your moment. Join us and lead the movement that’s transforming how the world sleeps and what we’re all capable of when we wake up.High Standards. No Apologies.We operate with intensity because our mission demands it. At Eight Sleep, we bring the same mindset as the world’s top performers: focused, relentless, and always pushing to be in the top 1% of our craft. Think Kobe Bryant’s mamba mentality, applied to bold ideas, next-gen tech, and flawless execution. This isn’t a 9-to-5. Our team is deeply committed, often putting in 60+ hours a week –not because we’re told to, but because we’re invested. We’re here to build fast, push limits, and deliver without compromise. If you thrive under pressure and want to do the most meaningful work of your career, you’ll feel right at home. If you’re looking for something easier –this isn’t it.The RoleWe’re seeking a Data Scientist to join our Data & Analytics team within the Growth organization. This isn't a typical analyst role - you'll be the lead growth data scientist at Eight Sleep, owning complex forecasting challenges that directly impact our supply chain, marketing spend, and business growth. The ideal candidate has deep experience with time series forecasting, experimentation design, and translating ambiguous business problems into data-driven solutions.What You'll BuildAdvanced demand forecasting models to solve our biggest operational challenge: eliminating stock-outs during peak periods (Black Friday, holidays) while avoiding overcommitting capital on inventoryMarketing spend optimization algorithms that go beyond our current Prophet model, incorporating seasonality, macro trends, and cross-channel effects to improve our CAC targetingExperimentation frameworks for incrementality testing across our marketing channels (Meta, Google, YouTube) with proper statistical rigorMarketing attribution models that handle our complex customer journey and multi-touch attribution challengesWhat You'll Need to Succeed 5+ years of data science experience with demonstrable impact on business-critical forecasting and optimization problemsForecasting expertise - you've built production models that handle seasonality, growth trends, and external factors. Bonus points if you've worked with Prophet and know its limitationsStrong experimentation background - you can design proper A/B tests, understand incrementality measurement, and have experience with marketing mix modelingAdvanced Python/R skills plus expert SQL - you'll be building production pipelines and complex models, not just ad-hoc analysisHigh ownership mentality - comfortable with ambiguous problems and 60+ hour weeks during critical periods. This is a startup where your work directly impacts our trajectoryBusiness acumen - you can translate between technical solutions and business stakeholders (Growth, Finance, Operations teams)Strong written and verbal communication - you can translate complex findings into actionable insights. Your written and verbal communication skills are excellentHigh sense of agency - you are an independent self-starter who thrives in a fast-paced environment and is comfortable owning a high level of responsibilityWe will hire for this role anywhere in the US, but working hours will be EST. Note: Employees approved for remote work must perform their duties from a single, company-approved based location #LI-RemoteWhy join Eight Sleep?Innovation in a culture of excellenceJoin us in a workplace where innovation isn’t just encouraged - it’s a standard. Our flagship product, the Pod, is a testament to our culture of excellence, beloved by hundreds of thousands of customers worldwide. At Eight Sleep, you will be part of a team that continuously pushes the boundaries of technology in sleep fitness.Immediate responsibility and accelerated career growthFrom your first day, you’ll take on substantial responsibilities that have a direct impact on our core business and product success. We are a small team that empowers you to own your projects and see the tangible effects of your efforts, enhancing both your professional growth and our company’s trajectory. Your path will be challenging but rewarding, perfect for those who thrive in fast-paced environments aiming for high standards.Collaboration with exceptional talentWork alongside other bright minds like you: at Eight Sleep exceptional intelligence and a passion for breakthroughs are the norms. Our team members are not only experts in their fields but also avid innovators who thrive in our dynamic, fast-paced environment.Equitable compensation and continuous equity investmentWe extend equity participation to every full-time team member, recognizing and rewarding your direct contributions to our success. This includes periodic equity refreshments based on performance, ensuring that as Eight Sleep grows and succeeds, so do you – perfectly aligning your achievements with the broader triumphs of the company. Pay grows rapidly as you accumulate experience with Eight Sleep and translate it into concrete impact.Your own Pod - and other great benefitsEvery Eight Sleep employee receives the very product that defines our mission: a Pod of their own. If you join us you’ll get your own Pod, along with*:Full access to health, vision, and dental insurance for you and your dependentsSupplemental life insuranceFlexible PTOCommuter benefits to ease your daily commutePaid parental leave*List of benefits may vary depending on your location

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About ElevenLabsElevenLabs is an AI research and product company transforming how we interact with technology.We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms:ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.ElevenAPI gives developers access to our leading AI audio foundational models.Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.How we workHigh-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.Excellence everywhere: Everything we do should match the quality of our AI models.Global team: We prioritize your talent, not your location.What we offerInnovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities.Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy.Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.About the roleAs a Forward Deployed Engineer Strategist, you'll work as part of a driven and creative team of Engineers, Product Designers, and other Strategists to deploy our voice AI technology against the most challenging problems our customers face. Your mission is to synthesize disconnected streams of thought into a cohesive understanding of what the most important problem is, what the data means, what the product needs, what users are motivated by, and where the impact could be.No two days are the same, but as a FDE Strategist you can expect to:Meet with strategic customers to understand their critical audio and voice AI needs and locate their biggest pain points.Identify relevant use cases through deep engagement with customer problems and workflows, and work with Engineers to implement our voice and audio AI technology into innovative solutions.Design and architect bespoke integrations for customers, ensuring our technology fits seamlessly into their products and operations.Guide customers on best practices for implementing our voice and audio AI models to maximize their effectiveness.Present the results of our work and proposals for future work to audiences ranging from technical teams to C-suite executives.Collaborate with our Research and Product teams to incorporate field insights into ElevenLabs' software products and AI models.Build and deliver compelling demos of our voice and audio AI technology to new and existing customers.Scope out potential applications in new industries and expand our AI solutions across different sectors globally.Take full ownership of end-to-end execution of major projects for our most strategic partners, working hands-on to deliver high-impact solutions.Collaborate daily with our customers' engineering and executive teams to ensure optimal implementation of ElevenLabs' technologies.RequirementsExperience working with customers in a technical capacity. It's ok if you only worked with customers in student clubs or side projects, as long as you are interested in working closely with them.Basic proficiency in Python and understanding of API integration to implement scripts and help with prototyping/demo building.Excellent communication and problem-solving skills, especially in terms of ability to summarize complex technical concepts and using logic in pursuing optimal solutions.A proven track record of taking ownership of complex projects and delivering results.Adaptability to work across different customer environments and technical use cases.Technical aptitude to quickly understand our voice and audio AI models and their applications.LocationThis role is remote and can be executed globally. If you prefer, you can work from our offices in Bangalore, Dublin, London, New York, San Francisco, Tokyo, and Warsaw.#LI-Remote

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level automotive engineering problems grounded in real practice; Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); Improve AI reasoning to align with first principles and accepted engineering standards; Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. 3+ years of professional automotive engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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About the RoleYou will architect, build, and scale the internal technology ecosystem that accelerates workforce productivity, eliminates operational friction, and gives the company a compounding infrastructure advantage. You will treat internal tools with the same product rigour and user-centricity as any external product — because the quality of internal systems directly determines organisational velocity.You will lead a cross-functional engineering team, make high-stakes build-vs-buy decisions, and drive AI adoption into internal workflows. This role requires someone who can see the company’s operational architecture as a system design problem and solve it with software.What You Will DoInternal Platform Strategy & RoadmapOwn the end-to-end strategy and roadmap for all internal tools, platforms, and automation — treating internal technology as a product, not a cost centre.Make strategic build-vs-buy decisions, knowing when a custom-built solution creates a lasting advantage and when a SaaS tool is the right answer.Map current and next-state process flows across the entire internal toolchain and lead systems transformation for internal teams.Systems Architecture & EngineeringArchitect and maintain the full engineering lifecycle for internal platforms — from ideation and design through deployment, iteration, and deprecation.Build seamless, API-first ecosystems that integrate internal tools across HR systems, finance platforms, knowledge management, CRM, and developer infrastructure.Own system reliability and operational resilience: establish success metrics for uptime, performance, and employee productivity.Design scalable, secure architectures using cloud-native principles, microservices, and modern integration patterns.AI & AutomationLead the strategy for integrating AI and LLMs into internal workflows — reimagining how knowledge is shared, decisions are supported, and work is executed across the organisation.Deploy intelligent automation tools — including AI where appropriate — to streamline internal processes and improve decision-making.Evaluate and integrate AI-assisted troubleshooting, proactive recommendations, and intelligent automation into the internal platform layer.Stay ahead of technology trends and drive continuous experimentation — you build prototypes, not slide decks.Developer Experience & ProductivityReduce cognitive load for internal users by providing golden paths, standardised workflows, and self-service capabilities.Ensure frictionless onboarding and seamless integration across the tool ecosystem.Measure platform success through adoption rates, user satisfaction, DORA metrics, and productivity impact — not feature count.Team LeadershipBuild, lead, and mentor a high-performing team of engineers and engineering managers.Cultivate a collaborative engineering culture rooted in ownership, speed, and craftsmanship.Provide technical mentorship and create growth paths for individual contributors and managers alike.Foster psychological safety and a feedback-driven environment that empowers people to do their best work.Cross-Functional CollaborationPartner with People, Finance, Engineering, Legal, and Operations leadership to translate complex business needs into a unified technical vision.Serve as the bridge between business stakeholders and the engineering team — you speak both languages fluently.Align internal platform investments with broader company strategy and demonstrate measurable ROI.What You Will NeedMust-Have12+ years of experience in software engineering, with at least 5 years in engineering leadership (managing teams or managing managers).Strong hands-on technical background: you’ve built production systems and can still credibly review architecture, code, and system design.Deep understanding of cloud-based systems (AWS, GCP, or Azure), APIs, microservices, data pipelines, and modern infrastructure.Proven track record of building and scaling internal tools or platforms that serve cross-functional business teams — not just engineering.Experience making build-vs-buy decisions and managing a portfolio of custom-built and third-party tools.Strong experience designing and building internal platforms and automation systemsStrong product thinking: you define success in terms of user outcomes and business impact, not technical output.Experience navigating the full SDLC from ideation through deprecation — you know when to build, iterate, and retire.Excellent communication skills: you can articulate complex technical concepts to non-technical executives and translate business problems into engineering roadmaps.Nice-to-HaveExperience at a high-growth technology or AI-native company that scaled rapidly.Background in platform engineering, developer experience, or internal developer platforms (IDPs).Familiarity with HRIS, ERP, and business systems integration (Workday, Salesforce, NetSuite, etc.).Experience with cybersecurity best practices and compliance frameworks for internal systems.Prior experience leading internal technology through M&A integrations or multi-entity consolidation.Exposure to knowledge management systems, internal search, and enterprise AI assistants.Experience integrating AI/LLMs into internal workflows or productivity toolsWhat Success Looks LikeWithin 30 days: Completed a full audit of the existing internal toolchain, identified the top friction points, and presented a prioritised roadmap.Within 60 days: Shipped at least two high-impact internal tools or automations that measurably improve productivity, and established team operating rhythm.Within 12 months: The internal tools ecosystem is a recognised competitive advantage — teams actively request new capabilities, AI is embedded in daily workflows, and internal NPS is consistently high.Who You AreAn engineer who thinks like a CEO. You’ve built production systems, led engineering teams, and understand that the best internal tools don’t just save time — they change how an organisation thinks and moves. You’re obsessed with removing friction, allergic to manual workarounds, and energised by the idea that great internal infrastructure compounds into organisational speed. You believe internal tools deserve the same craft as customer-facing products. You see AI not as a buzzword but as the most important lever for internal productivity in a generation, and you want to be the person who pulls it.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, the process to offer may be shorter.

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you.com is an AI-powered search and productivity platform designed to empower users with personalized, efficient, and trustworthy search experiences. As a cutting-edge technology company, we combine advanced AI models with user-first principles to deliver tools that enhance discovery, creativity, and productivity. At you.com, we are on a mission to create the most helpful search engine in the world—one that prioritizes transparency, privacy, and user control. We’re building a team of innovators, problem-solvers, and visionaries who are passionate about shaping the future of AI and technology. At you.com, you’ll have the opportunity to work on impactful projects, collaborate with some of the brightest minds in the industry, and grow your career in an environment that values creativity, diversity, and curiosity. If you’re ready to make a difference and help us revolutionize the way people search and work, we’d love to have you join us!  About the Role AI is transforming how enterprises sell, support, and operate — surfacing hidden knowledge, automating workflows, and collapsing weeks of effort into minutes. As an AI Engineer, Enterprise Solutions, you’ll act like a startup CTO, turning this vision into robust, production-ready AI solutions that ship fast and deliver measurable wins for our customers. You will get a front seat to AI applications in the economy along with defining and shaping the future.   Responsibilities  Build and Ship: Design and develop AI applications primarily in Python. Run evaluations to validate models and package solutions for Kubernetes, AWS, or adapt them to customer on-premises clusters. Work with Customers: Lead discovery sessions, guide pilot projects, and ensure successful deployments. Collaborate mostly remotely with occasional on-site workshops. Run and Improve: Monitor system performance and reliability. Add to the logging, billing and auth services. Build internal tooling to automate repetitive tasks. Share What You Learn: Provide feedback on patterns, pain points, and reusable modules to the core product team to influence the future direction of the AI platform.   Qualifications Required: 2+ years of experience writing solid production-quality software. Hands-on experience with LLMs and a solid understanding of machine learning fundamentals. Strong customer empathy: ability to listen, ask insightful questions, and translate real-world pain points into intuitive technical designs. Product-minded approach: focus on outcomes, comfortable shaping scope with product managers, defining success metrics, and making trade-offs to accelerate learning. Excellent communication skills, able to engage effectively with executives and engineers both remotely and on-site. Versatile problem-solver who thrives in ambiguous environments and enjoys rapid learning. Nice to Have: Experience in forward-deployed or product-oriented roles. Exposure to regulated industries such as healthcare or finance. Proficiency with Terraform or Pulumi and experience across multiple cloud platforms. Experience integrating with ERP, CRM, or other large enterprise systems. Our salary bands are structured based on a combination of geographic tiers and internal leveling. Compensation is determined by multiple factors assessed during the interview process, with the final offer reflecting these considerations.Salary Band$165,000—$200,000 USDCompany Perks: Hubs in San Francisco and New York City offering regular in-person gatherings and co-working sessions Flexible PTO with U.S. holidays observed and a week shutdown in December to rest and recharge* A competitive health insurance plan covers 100% of the policyholder and 75% for dependents* 12 weeks of paid parental leave in the US* 401k program, 3% match - vested immediately!* $500 work-from-home stipend to be used up to a year of your start date* $1,200 per year Health & Wellness Allowance to support your personal goals* The chance to collaborate with a team at the forefront of AI research *Certain perks and benefits are limited to full-time employees only You.com participates in E-Verify. We will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s Form I-9 to confirm work authorization. (English/Spanish: E-Verify Participation/Right to Work) We are also an inclusive, equitable, and accessible workplace. Please let us know if you require accommodation for any portion of the recruitment and hiring process. Beware of recruiting scams: You.com will only contact you through official @You.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

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About Basis Basis builds real agents that do real work in the real economy. Our agents operate for hours at a time, performing end-to-end work for some of the largest accounting firms in the world. Members of Technical Staff build the agents, the infrastructure they run on, and the product interfaces users work with. We recently raised $100M at >$1B valuation and are racing to deploy the most advanced applied ML at production scale. Our investors include: Khosla Ventures (Keith Rabois & Vinod Khosla), Accel (Miles Clements), Google Ventures, Nat Friedman & Daniel Gross, Adam D'Angelo, Jeff Dean, Jack Altman, Noam Brown, Kyle Vogt, Amjad Masad, Clem Delangue and many other operators/technical leaders. "Basis is on the frontier of building production-grade, long-horizon agents. They've pushed the limits of what we thought our models could do on real-world, economically valuable, complex accounting tasks. They've been a great collaborator in helping us shape what the future of agents looks like." — Prashant Mital, Applied AI Lead, OpenAIAbout the roleSpearhead our most complex problemsWhy Join Basis? We offer a competitive and thoughtful benefits package designed to support your physical, mental, and financial well-being:Health & Wellness: Premium Medical, Dental, and Vision coverage; Life Insurance; and 6 coaching & 6 therapy sessions through Spring Health.Time off: Unlimited PTO + 12 paid company holidays.In-Office Perks: Daily meal stipends, a fully stocked kitchen, and $300 toward your custom desk setup.Financial Benefits: Pre-tax commuter benefits and 401(k) retirement planTeam Culture: Monthly office activities and frequent optional team happy hours.Parental Leave

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!About Cohere and NorthCohere is revolutionizing enterprise AI with North, an agentic AI platform designed to securely deploy AI agents and automations within organizations' infrastructure. North empowers employees to streamline workflows, automate repetitive tasks, and unlock actionable insights while ensuring data privacy and compliance. North combines cutting-edge generative and search models with customizable integrations to drive productivity and innovation at scale.Role OverviewWe are seeking a Safety Research PM to bridge Cohere's AI safety research and the North product. This role sits at the intersection of model research and product delivery — you'll work directly with Cohere's modeling and safety research teams to understand how our models behave, where they fall short, and how those insights translate into concrete safety features and guardrails within North.This isn't a traditional PM role. You'll spend as much time reading evaluations and engaging with researchers as you will writing PRDs. The right person is intellectually curious, comfortable with ambiguity, and has the technical depth to engage seriously with model behavior research while also having the product instincts to know what to do with it.ResponsibilitiesServe as the product bridge between Cohere's safety research teams and North, ensuring that findings from model evaluations, red-teaming, and behavioral research translate into product-level guardrails, controls, and safeguards.Own the safety product roadmap for Cohere and North, prioritizing features based on research findings, observed misuse patterns, evolving threat vectors, and customer requirements.Partner with modeling teams to scope and interpret safety evaluations — understanding how Cohere’s underlying models behave across adversarial inputs, edge cases, and high-stakes use cases.Define and drive evaluation frameworks for assessing how safety properties hold up as models and product capabilities evolve, ensuring regressions surface before they reach customers.Coordinate the development of guardrails and intervention mechanisms — working across research, engineering, and policy to determine where and how safety controls should be implemented within North's product layer.Monitor the AI safety research landscape — from prompt injection and jailbreaks to emerging misuse patterns in agentic systems — and ensure North's roadmap reflects what the research is surfacing.Build processes for scaling safety review as North's surface area grows, including how new features get assessed for safety risk before launch.Requirements5+ years of product management or research operations experience, with meaningful time working alongside research or ML teams at a technology or AI company.Technical depth sufficient to engage credibly with safety researchers: you don't need to run evals yourself, but you need to understand what they mean and ask the right questions.Genuine interest in AI safety and model behavior, including the real-world implications of deploying LLMs in enterprise contexts.Comfortable operating in ambiguity — safety research surfaces unexpected findings, and this role requires good judgment about what to act on and how fast.Able to work across researchers, engineers, and product teams and keep everyone aligned without flattening the nuance of what the research is actually saying.Strong written communicator who can translate complex model behavior findings for non-technical audiences and knows when something needs to be escalated urgently.Nice-to-HavesHands-on experience with LLM evaluation, red-teaming, safety benchmarking, or behavioral research.Familiarity with AI-specific threat vectors: prompt injection, jailbreaks, RAG poisoning, or misuse patterns in agentic systems.Background in trust and safety, content policy, or a research-adjacent operational role at a technology company.Experience building zero-to-one processes in research or safety contexts.Prior exposure to agentic AI systems and the unique safety challenges introduced by tool use, multi-step reasoning, and autonomous execution.Why Join Cohere?Impact: Shape how one of the most widely deployed enterprise AI platforms thinks about and implements safety at the product level.Innovation: Work directly alongside safety researchers and modeling teams at the frontier of AI behavior research.Growth: Competitive compensation, equity options, and opportunities for professional development.Flexibility: Hybrid work model with offices in San Francisco, New York, and Toronto.LocationRemote or hybrid (New York, Toronto, London, Paris, Zurich).If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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About the roleAs a Full-Stack Engineer at Flowith, you will be at the intersection of front-end and back-end development, building robust, scalable, and user-friendly AI-powered products. Your work will directly impact how our users interact with complex AI capabilities, transforming advanced algorithms into intuitive features. You'll collaborate cross-functionally with designers, product managers, and other engineers to deliver seamless experiences that bring our AI products to life.Responsibilities:End-to-End Product Building: Cross the front-end and back-end boundaries to independently or collaboratively lead the full-stack development of Flowith's core modules, delivering highly available and scalable system code.AI Engine Integration: Deeply integrate advanced AI algorithms and complex models into the product flow, breaking down technical barriers to create stunning, intelligent interactive experiences.Cross-Functional Agile Collaboration: Work tightly with product managers, designers, and AI engineers in a highly creative atmosphere to bring wild, visionary AI concepts down to earth.Cloud Deployment & Performance Tuning: Automate deployments and manage continuous integration on mainstream cloud infrastructure, constantly monitoring and optimizing system performance and resource bottlenecks.Defending Engineering Standards: Participate in the evolutionary design of the core architecture and conduct in-depth Code Reviews, continuously accumulating technical components and best practices to elevate the team's overall engineering standards.工作内容：跨越前后端边界，独立或协同负责 Flowith 核心功能模块的全栈开发，交付高可用、可扩展的系统代码。将先进的 AI 算法与复杂模型深度整合到产品流中，打破技术壁垒，创造令人惊艳的智能化交互体验。与产品经理、设计师及算法工程师深度咬合，在充满创造力的氛围中，将天马行空的 AI 理念落地生根。在主流云基础设施上进行应用的自动化部署与持续集成，时刻监控并优化系统性能与资源瓶颈。参与核心架构的演进设计与深度的 Code Review，持续沉淀技术组件与最佳实践，提升团队整体的工程化水位。RequirementsRequired qualifications:At least 3 years of full-stack web development experience.Proficiency in JavaScript and TypeScript, with hands-on experience in at least one major front-end framework (React, Vue, Angular).Solid experience in back-end development, with expertise in one or more back-end languages (Node.js, Python, Go, Java).Familiarity with at least one mainstream database system and strong data modeling skills.Hands-on experience deploying and maintaining applications on cloud platforms such as AWS, GCP, Azure, or Cloudflare.Deep understanding of software engineering principles, system design, and code quality.Passion for AI/ML products and the ability to distill complex AI capabilities into intuitive features.Bonus pointsPractical experience productizing large language models (LLMs).Familiarity with serverless computing and microservices architecture.Active contributions to open source projects, personal blogs, or a strong presence on GitHub.Insight into user experience (UX) design and product usability. 需要你： 3 年及以上全栈 Web 开发经验。具备深厚的软件工程底蕴，精通系统设计，并对优雅的代码质量有极致的强迫症。精通 JavaScript 和 TypeScript，在至少一种主流前端框架（React、Vue 或 Angular）上有丰富的实战经验，能写出丝滑的交互体验。具备扎实的后端架构与开发经验，精通 Node.js、Python、Go 或 Java 中的一种或多种语言。熟悉至少一种主流数据库系统，具备极强的数据建模与性能调优能力。拥有在 AWS、GCP、Azure 或 Cloudflare 等云平台上部署和维护高可用应用的实战经验。对 AI/ML 产品充满狂热，具备极强的同理心，能将晦涩复杂的 AI 能力“翻译”成用户爱不释手的直观功能。加分项：有大型语言模型（LLMs）产品化落地的实战经验；熟悉 Serverless 计算与微服务架构；在开源社区活跃（有高亮 GitHub 主页、技术博客或开源贡献）；拥有敏锐的 UX 嗅觉，懂设计和产品可用性。BenefitsWorkspace, Culture & LifestyleAwesome Teammates: Work alongside a kind, creative, and hardworking crew of occasional "geeks" and visionaries.Building the AGI Future: Participate in the in-house development of rapidly evolving AI agents and explore the future of AGI interactive interfaces.Cool Offices in SH & SF: Enjoy our ultra-open workspaces with the ultimate freedom to seamlessly switch between our Shanghai and San Francisco locations.Pet-Friendly Workplace: Bring your furry friends to work! Come play with our resident Orange Tabby and Golden Retriever Mix, or bring your own pets to hang out.Island Hackathons: Join our annual internal hackathons, where we select a new city or country each year for innovative coding sessions and team bonding.Free AI Tools & Tech Gear: Enjoy free, unlimited access to cutting-edge AI tools, plus the latest tech equipment like Apple Vision Pro and FPV drones.Tech Events: Regularly participate in top-tier global tech meetups and innovation showcases.Parties & Events: Celebrate with monthly birthday bashes and annual milestone partiesFree Snacks & Drinks: Stay fueled with an endless supply of your favorite beverages and unlimited complimentary snacks.Work ArrangementsFlexible Working Hours: Customize your schedule by arriving at the office between 10 AM and 1 PM for a standard 8-hour workday, 5 days a week.Remote Work & Care: Embrace a supportive hybrid work model, featuring 1 additional Work-From-Home (WFH) day per month exclusively for female employees.Comprehensive Benefits PackageCompetitive Compensation: Earn an above-market salary structure with an optional equity/stock options package.Wellness Program: Take care of your body and mind with free gym access and monthly on-site professional massages.Exclusive Swag & Perks: Receive holiday surprise gift boxes, premium custom company apparel (T-shirts, hoodies, and jackets), and occasional exclusive internal brand discounts.

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About the RoleA1 is building a proactive AI system that carries work forward across conversations, tools, and time — enabling users to delegate ongoing tasks to AI agents that coordinate across software, data, and workflows.We are looking for a leader who can think clearly about systems, make strong technical decisions, and help build the engineering organisation from the ground up.Be part of founding team to shape the technical direction of the company, while helping build a strong engineering team across the globe.What You'll DoTechnical DirectionDefine the long-term architecture for A1’s AI systems, infrastructure, and developer platformEvaluate trade-offs between speed of iteration and long-term system designEnsure systems are designed for scalability, reliability, and long-term evolutionGuide key decisions across model integration, data pipelines, distributed systems, and product architectureEngineering LeadershipWork with engineers to translate product direction into clear technical executionHelp structure engineering workstreams and keep teams aligned on prioritiesMaintain high engineering standards while keeping the team focused on shippingEstablish engineering culture, development practices, and technical standards across the companyBuilding the TeamBuild and scale a world-class engineering team across key talent hubs including China and USIdentify strong technical leaders and help build a high-quality engineering organizationDefine hiring standards and interview processes to maintain a high engineering barCoordination and ExecutionWork closely with product, research, and leadership teamsEnsure technical workstreams move forward smoothly across teams and locationsHelp resolve cross-team technical and execution challengesWhat You Will NeedStrong technical foundation in system architecture, large-scale systems, distributed architecture.Ability to reason clearly about complex systems and make pragmatic technical decisionsExperience building or leading high-performing engineering teamsStrong judgment on technical trade-offs and engineering prioritiesComfortable operating in early-stage environments with high ambiguityClear communication and ability to align teamsWe are particularly interested in candidates who enjoy building teams, superior products and shaping engineering organisations.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, the process to offer may be shorter.