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Company OverviewDeepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.Company Operating RhythmAt Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.OpportunityDeepgram is looking for a backend software engineer to lead the design and implementation of Deepgram’s Voice Agent product. You will design and implement secure, robust, and scalable services for speech processing; build integrations supporting telephony providers, RAG systems, and diverse deployment scenarios; engineer for testability and observability within a complex chain of AI models; and more. Your skill at building highly reusable code that overcomes technical challenges is paired with an intuition for delightful user experiences. You will be a critical voice in Deepgram’s Product and Engineering teams, driving high impact products from start to finish.What You’ll DoImprove Deepgram’s core inference services including areas in networking, speech processing, model orchestration, and observabilityDevelop integrations with cutting edge in-house, third-party, and open-source AI models for perception and managing conversational dynamicsDebug complex system issues that include networking, scheduling, and highly concurrent workloadsRapidly customize backend services to support our customer needsPartner with Product to design and implement new services, features, and/or products end to endYou’ll Love This Role If YouThrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessityEnjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design workIt’s Important To Us That You Have3+ years of experience in an industry roleProgramming experience in Rust (or C, C++), with competence in PythonExcellent communication and organizational skills, both written and verbal.A high level of experience and understanding of version control; preferably git.Comprehensive experience with UNIX-style systems.It Would Be Great If You HadExperience with low-latency, multi-model orchestration for AI-enabled applicationsExperience with audio processingBenefits & Perks*Holistic healthMedical, dental, vision benefitsAnnual wellness stipendMental health supportLife, STD, LTD Income Insurance PlansWork/life blendUnlimited PTOGenerous paid parental leaveFlexible schedule12 Paid US company holidaysQuarterly personal productivity stipendOne-time stipend for home office upgrades401(k) plan with company matchTax Savings ProgramsContinuous learningLearning / Education stipendParticipation in talks and conferencesEmployee Resource GroupsAI enablement workshops / sessions*For candidates outside of the US, we use an Employer of Record model in many countries, which means benefits are administered locally and governed by country-specific regulations. Because of this, benefits will differ by region — in some cases international employees receive benefits US employees do not, and vice versa. As we scale, we will continue to evaluate where we can create more alignment, but a 1:1 global benefits structure is not always legally or operationally possible.Backed by prominent investors including Y Combinator, Madrona, Tiger Global, Wing VC and NVIDIA, Deepgram has raised over $215M in total funding. If you're looking to work on cutting-edge technology and make a significant impact in the AI industry, we'd love to hear from you!Deepgram is an equal opportunity employer. We want all voices and perspectives represented in our workforce. We are a curious bunch focused on collaboration and doing the right thing. We put our customers first, grow together and move quickly. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, pregnancy, parental status, genetic information, political affiliation, or any other status protected by the laws or regulations in the locations where we operate.We are happy to provide accommodations for applicants who need them.

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About HandshakeHandshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feelWork hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsJoin a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among othersBuild a massive, fast-growing business with billions in revenueAbout the RoleWe’re expanding our team and seeking a Senior Engineering Manager to lead our Reinforcement Learning Environments (RLE) team.The RLE team builds the sandbox environments where frontier AI models learn complete, end-to-end workflows. These environments simulate real-world professional domains such as software engineering, finance, and legal research — complete with realistic tools, constraints, and feedback loops. Instead of learning from static examples, models practice doing the work: navigating multi-step tasks, using domain-specific tools, handling ambiguity, and optimizing for real outcomes.Researchers use these environments and the data they generate to train state-of-the-art models with reinforcement learning grounded in execution — not just prediction, but task completion, quality, and robustness in complex workflows.As a Senior Engineering Manager, you’ll shape the technical direction and long-term strategy of this critical platform. You’ll lead a growing team (currently 9 engineers) and will likely manage an Engineering Manager in the near term. This is a highly strategic role sitting at the intersection of platform engineering, applied AI infrastructure, research tooling, and human-in-the-loop operations systems.Location: San Francisco, CA| 5 days/week in-officeLead and grow a high-performing team of 8–9 engineers building reinforcement learning environmentsManage, mentor, and develop senior engineers and future engineering leadersPartner closely with research, product, and operations teams to define roadmap and execution prioritiesDrive technical architecture for scalable, reliable, and extensible environment systemsBuild plug-and-play environments that integrate seamlessly with model training pipelinesBalance platform rigor with operational complexity and data quality requirementsEstablish engineering best practices around reliability, observability, and performanceFoster a culture of ownership, velocity, and high technical standardsDesired Capabilities3+ years of engineering management experience, with increasing scope and ownershipExperience managing senior engineers; experience managing an Engineering Manager (or equivalent scope) strongly preferred5+ years of prior hands-on engineering experienceStrong technical background in platform systems, distributed systems, or full-stack infrastructureExperience building internal platforms, data pipelines, or research-facing toolsProven ability to operate effectively in fast-paced, ambiguous environmentsExperience driving cross-functional alignment across engineering, research, and operationsWillingness to work in-office in San Francisco 5 days/weekExtra CreditExperience in reinforcement learning, simulation systems, or AI training infrastructureBackground in human-in-the-loop systems, data annotation platforms, or workflow toolingExperience in operations-heavy, tech-enabled organizationsFamiliarity with cloud infrastructure (AWS or GCP), APIs, and modern web stacks (e.g., React, TypeScript, Node.js, Python)Experience building systems used by AI researchers or applied ML teamsWhat Success Looks LikeRLE becomes the default platform researchers use to train reinforcement learning workflowsNew domains (e.g., finance, legal, SWE) can be launched quickly and reliablyEnvironment reliability and data quality are trusted by top AI research partnersThe team scales with strong technical leaders who can independently drive new verticalsThe RLE platform materially accelerates model capability in real-world task completionPerksHandshake delivers benefits that help you feel supported—and thrive at work and in life.The below benefits are for full-time US employees.🎯 Ownership: Equity in a fast-growing company💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching🍼 Family Support: Paid parental leave, fertility benefits, parental coaching💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

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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 EmaEma is at the forefront of the agentic AI revolution, empowering enterprises to reimagine how work gets done. Our platform enables organizations to design, deploy, and manage fleets of AI employees—multi-agent systems with rich human-in-the-loop interfaces—that automate complex workflows, augment decision-making, and unlock new levels of efficiency and growth. We are a team of ambitious innovators, building the future of work, and we’re looking for passionate individuals to join us on this mission.The RoleThis is not a traditional, backlog-focused product management role. As an Agentic Solutions Product Manager, you’ll partner directly with enterprise leaders to observe and decode human workflows—what data they use, what applications they rely on, and what SOPs they follow. From this, you’ll craft AI employees: multi-agent workflows with intuitive, UI-driven human-in-the-loop controls that transform how businesses operate.You won’t just manage features; you’ll design and deliver entire AI-powered solutions. You’ll be a trusted advisor and a strategic co-creator, working at the intersection of business strategy, workflow design, and cutting-edge AI technology.What You Will DoUnderstand Human Workflows: Partner with enterprise customers to map end-to-end processes, uncover inefficiencies, and identify opportunities where agentic AI can create impact.Design AI Employees: Translate workflows into agentic multi-agent systems, integrating data, applications, and UI-driven human oversight.Bridge Business and Technology: Work hand-in-hand with engineering and design to turn client requirements into scalable agent capabilities and elegant product experiences.Drive Strategic Roadmaps: Own the lifecycle of your AI employees—from concept through deployment—guided by customer feedback, data, and business outcomes.Champion Adoption & Value: Ensure customers achieve measurable ROI, advocate for your solutions internally and externally, and evangelize the power of agentic AI.Continuously Optimize: Use data and customer insights to refine workflows, enhance capabilities, and identify new areas for automation and transformation. What We’re Looking ForEntrepreneurial Mindset: Self-starter who thrives in ambiguity, owns outcomes, and builds solutions from the ground up.Proven Client-Facing Experience: 4+ years in consulting, engagement management, product, or as a founder—trusted by senior stakeholders.Strategic Product Acumen: Ability to go beyond surface-level requests and solve the real business problem.Technical Credibility: Comfortable diving into architectural trade-offs, APIs, and agentic design with engineers.Systems Thinking: Natural ability to see the whole picture, anticipate downstream effects, and design resilient solutions. Preferred SkillsExperience in user research and workflow mapping, with a data-driven mindset.Familiarity with generative AI and agentic AI; hands-on experience designing agent-based systems is a plus.Ability to prototype quickly—comfortable with "vibe coding" to visualize solutions.Background in product management, consulting, or founding roles.Experience in agile development environments and tools (JIRA, Asana, etc.).Hands-on experience with APIs and working closely with technical teams.Degree in Computer Science, Engineering, Math, or equivalent experience. For California Based CandidatesThe standard base salary for this position is $135,000 to $200,000 annually.Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.

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About Nomic Nomic builds domain-specific AI agents for the built world — helping Architecture, Engineering, and Construction (AEC) teams across tasks like drawing reviews, takeoffs, code compliance, RFIs, submittals, specs, QA/QC, coordination, and project documentation. Our goal is to build AI systems that reflect how AEC work is actually done in practice—grounded in real workflows, real constraints, and real project complexity. About the Role We’re launching a Domain Experts in Residence (DEIR) program to embed experienced AEC practitioners directly into how our AI agents and workflows are designed, evaluated, and shipped. This is not a traditional advisory role. As a Domain Expert in Residence, you’ll be hands-on in defining real-world AEC tasks, building datasets, and shaping evaluation criteria that determine how our agents perform across the project lifecycle. This role is ideal for practitioners who want to shape the future of tools used by their profession. What You’ll Do Define real-world AEC task specifications for AI agents (e.g., drawing reviews, code compliance, RFIs, submittals, spec review, QA/QC, coordination)Create and label gold-standard datasets from real project artifacts (drawings, specs, RFIs, submittals)Design evaluation rubrics for agent outputs (severity, discipline, correctness, usefulness)Co-design default workflows that ship to customersPressure-test agents against real-world project scenarios and common failure modesPartner closely with product, ML, and engineering teams to translate domain practice into scalable AI systems Who You Are 6+ years of professional experience in one or more of:ArchitectureStructural EngineeringMEP EngineeringConstruction / Project ManagementQA/QC or Code ComplianceDeep familiarity with real AEC workflows and project deliverablesComfortable articulating how work is actually done in practiceCurious about AI tools and automation (no ML background required)Motivated to shape the future of AEC tooling Nice to HaveExperience with QA/QC processes or design reviewsFamiliarity with building codes (IBC, ADA, NFPA, local codes)Experience writing standards, checklists, or internal review frameworksInterest in product development Why This Role Is DifferentYou’ll help define how AI supports real AEC workflowsYour expertise will directly shape products used by real firmsYou’ll work closely with product and ML teamsYou’ll influence the next generation of tools for your profession CompensationCompetitive compensation based on experienceEquity for full-time rolesFlexible part-time options for specialists

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Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone. When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people.  As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif. Hardware Engineer I positions offered by Latitude AI, LLC (Palo Alto, CA).  What you’ll do:  Develop tools for validation and regression testing of image sensors, image processing pipelines, and hardware and software integration Perform lab and real-world camera data collection and data analysis Participate in tuning of sensor parameters and image processing pipelines to optimize image quality Troubleshoot camera and image quality issues observed on autonomous vehicles Design new hardware and the necessary software for sensor range Work with perception software team to assess end to end camera performance What you'll need to succeed: Requires a bachelor’s or foreign equivalent degree in Computer Engineering, Electrical Engineering, Mechanical Engineering, Physics, or a related field  Education, training, or experience must include: o Programming in Python; o Working with camera hardware and camera pipelines;  o Using Python to manipulate and analyze image data;  o Working with and debugging embedded hardware and software;  o Working with image quality metrics and evaluation methods;  o Working with Linux operating system; and  o Defining, documenting, executing, and analyzing complex tests.   Position reports to Palo Alto, CA office. Telecommuting permitted in accordance with company policy, but must live within commuting distance of stated office. Experience may be, but need not be, acquired concurrently. What we offer you: Competitive compensation packages High-quality individual and family medical, dental, and vision insurance Health savings account with available employer match Employer-matched 401(k) retirement plan with immediate vesting Employer-paid group term life insurance and the option to elect voluntary life insurance Paid parental leave Paid medical leave Unlimited vacation 15 paid holidays Daily lunches, snacks, and beverages available in all office locations Pre-tax spending accounts for healthcare and dependent care expenses Pre-tax commuter benefits Monthly wellness stipend Adoption/Surrogacy support program Backup child and elder care program Professional development reimbursement Employee assistance program Discounted programs that include legal services, identity theft protection, pet insurance, and more Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives Learn more about Latitude’s team, mission and career opportunities at lat.ai! The expected base salary range for this full-time position in California is $163,611 - $199,920 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements. Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position. We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. #LI-DNI

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About Air AppsAt Air Apps, we believe in thinking bigger—and moving faster. We’re a family-founded company on a mission to create the world’s first AI-powered Personal & Entrepreneurial Resource Planner (PRP), and we need your passion and ambition to help us change how people plan, work, and live. Born in Lisbon, Portugal in 2018—and now with offices in both Lisbon and San Francisco—we’ve remained self-funded while reaching over 100 million downloads worldwide.Our long-term focus drives us to challenge the status quo every day, pushing the boundaries of AI-driven solutions that truly make a difference. Here, you’ll be a creative force, shaping products that empower people across the globe.Join us on this journey to redefine resource management—and change lives along the way.The RoleAs an AI Product Manager at Air Apps, you will be at the forefront of shaping AI-powered applications that enhance user experiences. You will lead the product development lifecycle for AI-driven features, working closely with engineers, designers, and data scientists to develop, launch, and scale AI-driven solutions. Your role is pivotal in ensuring that AI technologies align with user needs and business objectives.Please note that this post serves the purpose of enhancing our talent pool while we prepare to launch the official job. As soon as it gets posted we will get in touch with you.ResponsibilitiesDefine and drive the AI product roadmap, ensuring alignment with business objectives and user needs.Collaborate with cross-functional teams, including engineering, design, and marketing, to develop and launch AI-powered features.Conduct market research and analyze user feedback to identify opportunities for AI integration.Work closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact.Define key performance indicators (KPIs) to measure success and iterate based on data-driven insights.Stay up to date with AI trends, emerging technologies, and best practices to ensure our products remain competitive.Ensure ethical AI usage and compliance with data privacy regulations.RequirementsAround 4+ years of experience in product management, preferably in AI, machine learning, or data-driven applications.Strong understanding of AI/ML concepts, including NLP, computer vision, and recommendation systems.Experience working with data science and engineering teams to develop AI-based features.Ability to translate complex AI concepts into user-friendly applications.Strong analytical skills and experience leveraging data to drive product decisions.What benefits are we offering?Apple hardware ecosystem for work.Annual BonusTop-tier Health and Life Insurance for peace of mind.Transportation Budget to support your commute needs.Coverflex benefits package for meal allowances, well-being, and more.Childcare support.Air Conference - an opportunity to meet the team, collaborate, and grow together.Pension Fund to support your long-term financial planning.Urban Sports Club membership to keep you active.Meals 100% free at the hub.Diversity & InclusionAt Air Apps, we are committed to fostering a diverse, inclusive, and equitable workplace. We enthusiastically welcome applicants from all backgrounds, experiences, and perspectives. We celebrate diversity in all its forms and believe that varied voices and experiences make us stronger.Application DisclaimerAt Air Apps, we value transparency and integrity in our hiring process. Applicants must submit their own work without any AI-generated assistance. Any use of AI in application materials, assessments, or interviews will result in disqualification.

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About Air AppsAt Air Apps, we believe in thinking bigger—and moving faster. We’re a family-founded company on a mission to create the world’s first AI-powered Personal & Entrepreneurial Resource Planner (PRP), and we need your passion and ambition to help us change how people plan, work, and live. Born in Lisbon, Portugal in 2018—and now with offices in both Lisbon and San Francisco—we’ve remained self-funded while reaching over 100 million downloads worldwide.Our long-term focus drives us to challenge the status quo every day, pushing the boundaries of AI-driven solutions that truly make a difference. Here, you’ll be a creative force, shaping products that empower people across the globe.Join us on this journey to redefine resource management—and change lives along the way.The RoleAs an AI/ML Engineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications. You will work closely with product managers, engineers, and designers to create intelligent, data-driven features that enhance user experiences. Your expertise in artificial intelligence and deep learning will help us innovate and stay ahead in the mobile app industry.Please note that this post serves the purpose of enhancing our talent pool while we prepare to launch the official job. As soon as it gets posted we will get in touch with you.ResponsibilitiesDevelop, train, and optimize machine learning models for various mobile app features.Research and implement state-of-the-art AI techniques to improve user engagement and app performance.Collaborate with cross-functional teams to integrate AI-driven solutions into our applications.Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring.Analyze large datasets to derive insights and drive data-driven decision-making.Stay updated with the latest AI trends and best practices, incorporating them into our development processes.Optimize AI models for mobile environments to ensure high performance and low latency.RequirementsAround 4+ years of experience in AI/ML development, preferably in mobile applications.Proficiency in Python, TensorFlow, PyTorch, or other ML frameworks.Experience with deep learning, NLP, computer vision, and statistical modeling.Familiarity with cloud-based ML services (AWS, Google Cloud, or Azure).Strong understanding of data structures, algorithms, and software engineering best practices.Experience in deploying and maintaining ML models in production.Ability to work collaboratively in a remote team environment.Strong problem-solving skills and a passion for innovation.What benefits do we offer?Apple hardware ecosystem for work.Annual BonusTop-tier Health and Life Insurance for peace of mind.Transportation Budget to support your commute needs.Coverflex benefits package for meal allowances, well-being, and more.Childcare support.Air Conference - an opportunity to meet the team, collaborate, and grow together.Pension Fund to support your long-term financial planning.Urban Sports Club membership to keep you active.Meals 100% free at the hub.Diversity & InclusionAt Air Apps, we are committed to fostering a diverse, inclusive, and equitable workplace. We enthusiastically welcome applicants from all backgrounds, experiences, and perspectives. We celebrate diversity in all its forms and believe that varied voices and experiences make us stronger.Application DisclaimerAt Air Apps, we value transparency and integrity in our hiring process. Applicants must submit their own work without any AI-generated assistance. Any use of AI in application materials, assessments, or interviews will result in disqualification.

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About the TeamOpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Applied Voice Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems.About the RoleAs a Research Engineer in OpenAI's Applied Voice Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible solutions in B2B applications, API and ChatGPT AVM. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.In this role, you will:Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.You might thrive in this role if you:Master's/ PhD degree in Computer Science, Machine Learning, or a related field.2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies.Demonstrated experience in deep learning and transformers modelsProficiency in frameworks like PyTorch or TensorflowStrong foundation in data structures, algorithms, and software engineering principles.Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimizationExperience with speech models is a plus.Excellent problem-solving and analytical skills, with a proactive approach to challenges.Ability to work collaboratively with cross-functional teams.Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlinesEnjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.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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Crusoe's mission is to accelerate the abundance of energy and intelligence. We’re crafting the engine that powers a world where people can create ambitiously with AI — without sacrificing scale, speed, or sustainability.Be a part of the AI revolution with sustainable technology at Crusoe. Here, you'll drive meaningful innovation, make a tangible impact, and join a team that’s setting the pace for responsible, transformative cloud infrastructure.About the Role As a Senior Staff Cloud Support Engineer, you are a technical authority within Crusoe Cloud and a force multiplier across Customer Experience, SRE, Networking, Fleet, and Product teams. You operate beyond ticket resolution. You design reliability guardrails, influence architecture decisions, mentor senior engineers, and directly protect revenue by preventing large-scale incidents. You bring deep expertise in Linux systems, Kubernetes, networking, and AI/ML infrastructure, and apply that knowledge with strong customer focus. You are comfortable operating in ambiguity, leading incident response, and shaping how Crusoe scales high-performance AI infrastructure globally. What You’ll Be Working On Technical Leadership & EscalationsServe as highest-level escalation point for complex P1/P0 incidents.Lead cross-functional root cause investigations involving compute, networking (IB/RDMA/RoCE), storage, and orchestration layers.Partner with SRE, Software teams (Storage, Networking, Compute, K8) to design systemic fixes rather than recurring workarounds.Reliability ArchitectureDesign and improve node validation, burn-in processes, performance baselining, and release readiness.Influence Kubernetes architecture, workload orchestration (Slurm, Terraform), and AI/ML cluster stability.Reduce MTTR and incident recurrence through structural improvements.AI/ML Infrastructure ExpertiseTroubleshoot NCCL, IB, GPU driver/firmware issues, distributed training failures.Support complex AI workloads (training + inference) with performance tuning and observability improvements.Customer-Facing AuthorityAct as senior technical advisor during high-risk customer incidents.Deliver executive-ready RCAs with clarity and confidence.Drive trust through transparency and technical depth.Mentorship & StandardsMentor P3/P4 engineers.Define SOPs and technical standards for support excellence.Partner with Enablement to raise the technical bar across the organization. What You Bring8+ years experience in SRE, DevOps, HPC, or Cloud Infrastructure roles.Advanced Linux systems expertise.Deep Kubernetes operational experience (CKA-level or higher).Strong networking knowledge: Infiniband, RDMA, RoCE, SDN.Experience supporting AI/ML workloads at scale (GPU clusters).Proven track record of resolving multi-layer, distributed system failures.Strong customer communication and executive-facing presence.BenefitsIndustry competitive payRestricted Stock Units in a fast growing, well-funded technology companyHealth insurance package options that include HDHP and PPO, vision, and dental for you and your dependentsEmployer contributions to HSA accounts Paid Parental Leave Paid life insurance, short-term and long-term disability Teladoc 401(k) with a 100% match up to 4% of salaryGenerous paid time off and holiday scheduleCell phone reimbursementTuition reimbursementSubscription to the Calm appMetLife LegalCompany paid commuter benefit; $300/monthCompensation RangeCompensation will be paid in the range of up to $180,000 -$220,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data.Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

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About ClarionAt Clarion, we’re rebuilding how healthcare communicates in the age of AI.Today, clinics miss 30–40% of patient calls, while staff are overwhelmed by administrative work. We believe AI agents should handle these workflows—scheduling, billing, prescription refills, and follow-ups—so healthcare teams can focus on actual patient care.We’re building the communication infrastructure modern healthcare needs. Our AI agents don’t just answer calls—they complete workflows end-to-end, ensuring patients never go unheard. To date, we’ve handled hundreds of thousands of patient interactions across virtual care companies, health systems, and a $5B health insurance company.Clarion was founded by a Stanford/Harvard-trained physician (founding team at Two Chairs and Ophelia) and an ex-Amazon Alexa engineer who led AI/ML teams at Salesforce. We’ve raised $5.4M from Accel, Y Combinator, Sequoia (Scout), and leading healthcare founders. We’re an in-person team in New York, moving fast to solve one of healthcare’s most critical problems.Why This Role Is SpecialReal traction, early-stage impact: Dozens of paying customers, rapidly growing revenue, and the opportunity to own foundational backend systems at a critical inflection point.Mission-critical problem: Healthcare communication failures affect millions daily—your work directly powers systems patients and providers rely on.Elite technical context: Work closely with founders who deeply understand both healthcare operations and large-scale AI systems, enabling fast decisions and real ownership.What You’ll OwnCore backend systems: Design, build, and own the services, data models, and business logic powering Clarion’s AI agents and healthcare workflows.Workflow orchestration: Build infrastructure for multi-step, asynchronous workflows—including agentic AI workflows with conditional logic, retries, and graceful failure handling.Healthcare integrations: Own high-stakes integrations with EHRs and legacy healthcare platforms via APIs and RPA.Platform foundations: Create internal abstractions and tooling that allow the team to deploy and customize AI assistants for new customers quickly and reliably.Security and compliance: Implement and maintain backend authentication, authorization, and HIPAA-compliant architecture required for enterprise healthcare.Interesting Technical ChallengesGenerative AI at Scale: Design and operate production systems using LLMs with real-time monitoring, safety controls, and enterprise reliability.Agentic workflows: Architect backend systems that coordinate AI agents across complex healthcare workflows with strong guarantees.Enterprise reliability: Build systems supporting thousands of concurrent patient interactions with high uptime and fast incident detection.Fragmented healthcare systems: Design resilient abstractions across modern APIs and legacy EHRs while maintaining security and compliance.What We’re Looking For5+ years of experience designing, building, and scaling backend systems in high-reliability production environments.Strong backend expertise across APIs, relational databases, async workflows, and distributed systems.High ownership and agency—you thrive in ambiguity and take responsibility for system outcomes.Ability to communicate clearly, collaborate cross-functionally, and surface risks early.Bonus: experience with security, auth, or regulated environments (HIPAA familiarity is a plus).You’ll be a great fit if you enjoy owning critical backend systems end-to-end, solving complex problems under real-world constraints, and building infrastructure that directly impacts patient care.Interview ProcessWe move quickly and communicate clearly at every stage:Intro Chat (30 min, Virtual): Background, role context, and mutual fit.Technical Deep Dive (1 hr, Virtual): Backend systems and architecture with the CTO and a senior engineer.Onsite Team Day (Half Day, NYC): Collaborate on real problems, present a past project, meet the team, and assess mutual fit.Decisions are typically made within 24 hours of each stage.

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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!Cohere Labs is the dedicated research arm of Cohere. Our mission is to push machine learning forward through open, collaborative research and hands-on experimentation. We work on frontier problems in NLP and AI while creating space for researchers and engineers from different backgrounds to contribute, learn, and grow.We care about building things that are both thoughtful and useful, from new methods and datasets to tools that make research more accessible. Our team values curiosity, ownership, and practical impact over hype.Why join Cohere Labs?Cohere Labs brings together researchers and engineers to explore ambitious ideas and turn them into real systems. We focus on advancing machine learning while expanding access to applied research training and global collaboration.We pursue this mission in two ways:Creating open, collaborative research spaces where engineers and researchers work side-by-side on ambitious ML problems.Expanding access to applied research training, helping early-career engineers grow into strong research contributors.About the roleWe’re looking for Research Engineers who enjoy getting their hands dirty: building experiments, debugging models, scaling training pipelines, and turning research ideas into working systems. This is a highly practical role. You’ll work closely with scientists and other engineers to implement new methods, run large-scale experiments, and help shape the infrastructure that supports our research programs.You don’t need to have everything figured out yet. We care more about curiosity, strong fundamentals, and a willingness to learn quickly in a fast-moving research environment. You may be a fit if you:Have a strong engineering background in machine learning, NLP, or related areas (through a Master’s degree, industry experience, or equivalent hands-on work).Enjoy writing clean, reliable code and building systems that others can use and extend.Are comfortable experimenting, running ablations, analyzing results, and iterating quickly.Have experience with deep learning frameworks and model optimization techniques (PyTorch, distributed training, RLHF, finetuning, evaluation frameworks)Like collaborating closely with researchers and translating ideas into practical implementations.Are excited to grow your research instincts while staying grounded in engineering excellence.At Cohere Labs, research engineers are not just support roles. They are core contributors who help define how ideas become reality. If you want to work on meaningful problems, learn fast, and help build tools that shape the future of AI, we’d love to hear from you.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 Role: We are looking for an GTM Engineer where you won’t just be using our tools—you’ll be the "First Customer," building the AI-native systems that power our technical support, onboarding, and customer success engines.You will own the technical roadmap for how LangChain supports its users. Your goal is to drive massive case deflection and a premium onboarding experience by building autonomous agents that solve complex technical problems before a human ever needs to step in. This is a role for a builder-operator who can identify a friction point in the customer journey and ship a production-grade agentic solution to fix it.You Will:Architect Customer Agents: Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows.Drive Case Deflection: Analyze customer friction points and build self-service AI systems that significantly reduce support volume while improving the quality of the customer experience.Own the Domain: Act as the product owner and the technical muscle proactively identifying opportunities for improvement, propose architectures, and own the full lifecycle of the systems you build.Dogfood the Stack: Be a key member of the feedback loop for our product team. As you build complex systems for our customers, you’ll identify gaps in our frameworks and contribute back to the LangChain and LangGraph open-source ecosystem.Build Onboarding Workflows: Develop "AI-native onboarding" experiences that help enterprise customers move from prototypes to production faster by automating documentation retrieval and code generation.What we are looking for:AI-Native Developer: You have a deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops. You have likely already built with LangChain or LangGraph.Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production.Self-Directed "Founder" Mentality: You don't need a ticket to tell you what to fix. You are comfortable navigating ambiguity, identifying high-impact problems, and driving them to completion autonomously.Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications.Customer-Centric: You enjoy the intersection of high-level engineering and direct customer impact. You can translate a customer's technical pain point into a scalable system architecture.Nice to Haves:Expertise with LangSmith for evaluation and monitoring.Experience building or maintaining open-source projects.A background in technical consulting, solutions engineering, or high-growth GTM teams.Compensation:We offer competitive compensation that includes base salary, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance.Salary: $160K - $180K

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[MS/PhD Intern] AI Engineer (3개월/정규직 전환형)카메라 기반 End-to-End 자율주행과 Physical AI를 경험할 수 있는 기회! 42dot은 자율주행 기술 'Atria AI'를 개발하고 있으며, 2027년 말 레벨2+ 자율주행 기술이 양산 차량에 적용될 예정입니다. 끈질긴 집요함과 빠른 실행력으로 세상을 바꿀 인재를 기다립니다.Autonomous Driving Engineering42dot은 카메라 기반의 End-to-End 방식의 자율주행 소프트웨어와 저전력·고성능 임베디드 시스템을 개발하고 있으며, 최신 MLOps 시스템으로 자동화된 데이터 파이프라인을 구축했습니다. 또한 agile한 개발 프로세스를 통해 AI 모델 학습부터 실도로 검증 실험을 빠른 템포로 진행합니다.Role Overview 본 포지션은 Autonomous Driving Group의 정규직 전환형 Intern (MS/PhD) 으로, 연구 결과를 실제 양산 자율주행 시스템으로 연결하는 실전형 연구·개발 인턴십입니다.인턴십 기간 동안 단순 보조 업무가 아닌, 실제 양산을 목표로 하는 자율주행 시스템과 실차 데이터, 프로덕션 레벨의 코드 및 MLOps 환경을 기반으로 정규직 엔지니어와 동일한 수준의 문제를 End-to-End로 함께 해결합니다.What You'll Do 자율주행 시스템 핵심 기술에 대한 설계, 구현, 검증까지 End-to-End 수행실차 데이터 기반 알고리즘/모델 설계 및 검증시뮬레이션 및 실도로 실험을 통한 성능 분석 및 개선연구 결과를 실제 시스템에 적용 가능한 형태로 구현AD Group 내 실제 프로덕션 팀과의 긴밀한 협업을 통한 문제 해결Available Tracks최종 소속과 업무는 인턴십 및 인터뷰 과정에서 확인된 개인의 전문성, 연구 관심사 및 성장 방향과 조직별 니즈를 종합적으로 고려하여 결정될 예정입니다.[Physical AI]자율주행을 위한 인지(Perception) 및 행동 예측 ML 모델 구현 및 실험주행 데이터 전처리 및 학습 데이터셋 구성·분석모델 성능 평가 및 실험 결과 분석Failure Case 정리 및 성능 개선을 위한 실험[Sensor Fusion]카메라 등 센서에서 생성된 인지 결과를 활용한 Object-level Fusion 및 Tracking 구현실차 데이터 기반 Fusion 성능 분석 및 로그 분석C++ 기반 실시간 시스템에서 Fusion 로직 구조 이해 및 개선[SLAM]자율주행을 위한 SLAM 및 Localization 알고리즘 연구 및 개발카메라, IMU 등 센서 데이터를 활용한 기본적인 위치 추정 및 맵 생성실차 또는 시뮬레이션 데이터 기반 정확도·안정성 분석[AI Infrastructure]자율주행 및 ADAS 시스템을 위한 미들웨어 및 시스템 소프트웨어 설계·개발Linux 기반 환경에서 차량 소프트웨어 통합 및 디버깅·테스트 지원시뮬레이션, 자동화 스크립트 등 개발·검증 환경 구축 및 고도화[Data Platform]자율주행 데이터 수집, 처리, 분석 파이프라인 설계·개발모델 학습 및 평가 자동화를 위한 Data Flywheel 구축주행 로그 및 실험 결과 등 대규모 로그 분석을 통한 자율주행 성능 개선대규모 데이터셋을 관리하고 제공하기 위한 확장 가능한 자율주행 데이터 플랫폼 구축[VLA]자율주행 판단 및 제어를 위한 Vision-Language-Action(VLA) 모델 아키텍처 연구Triplane, Flex 등 다양한 Encoder 구조 실험 및 멀티모달 데이터 기반 모델 학습과 주행 판단 근거 (Rationale) 분석Open/Closed-loop 시뮬레이션 환경에서의 모델 검증 및 Failure Case 분석학습·평가 파이프라인 구축 및 Model/Simulation/Data 등 유관 부서와의 협업을 통한 End-to-End 연구 수행Interview Process서류전형 - 코딩테스트 - 1차 인터뷰 - 2차 인터뷰 - 최종합격전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.Additional Information본 포지션은 채용 연계형 인턴십으로, 인턴십 평가 결과에 따라 정규직 전환 여부를 검토합니다.인턴십은 3개월간 운영되며, 해당 기간 동안 full-time 근무를 원칙으로 합니다.정규직 전환 시에는 인턴십 종료 후 1개월 이내 입사가 가능해야 하며, 조정이 필요한 경우 별도 협의를 통해 결정할 수 있습니다.석사·박사과정 졸업 예정자 및 기졸업자, 또는 경력 1년 미만의 인원에 한하여 지원할 수 있습니다.전문연구요원의 경우, 전직이 가능한 대상자에 한해 지원할 수 있습니다.이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보 및 학교 또는 연구실의 연구 비밀을 침해하는 내용이 없도록 유의하시기 바랍니다.모든 제출 파일은 30MB 이하의 PDF 양식으로 업로드를 부탁드립니다. (이력서 업로드 중 문제가 발생한다면 지원하시고자 하는 포지션의 URL과 함께 이력서를 recruit@42dot.ai으로 전송 부탁드립니다.)인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다.장애인/보훈대상자는 관련 법령에 따라 우대합니다.해외 국적자의 경우, 체류 자격 상 정규직 입사가 가능한 분을 대상으로 합니다.제출한 지원서에 허위 사실이 포함된 경우, 합격이 취소될 수 있습니다..※ 지원 전 아래 내용을 꼭 확인해 주세요.42dot이 일하는 방식, 42dot Way 보러가기 →42dot만의 업무몰입 프로그램, Employee Engagement Program 보러가기 →

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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 Multi-Agents Mission Planning Engineer, you’ll design and implement the Guidance, Navigation, and Control algorithms that translate high-level mission goals into actionable guidance for autonomous robots and multi-agent systems. You’ll bridge cutting-edge research and field-ready autonomy, ensuring our systems are both intelligent and predictable in live operations.ResponsibilitiesDesign algorithms that decompose high-level missions into structured, solvable guidance tasks for autonomous robots.Develop and optimize mission and path-planning frameworks for autonomous systems.Build scalable backend integrations for mission guidance and execution.Run simulations and validation campaigns to assess autonomy consistency across diverse mission types.Partner with AI/ML, backend, and product teams to ensure algorithms are efficient, testable, and deployable in real-time environmentCandidate RequirementsEducation: Ph.D. or M.S. in Aerospace Engineering, Robotics, Applied Math, AI, or related field. A PhD in the field of multi-agent systems or reinforcement learning is a huge plus.Experience designing and deploying mission- or path-planning algorithms in aerospace, defense, or robotics is a huge plusTechnical Skills: Strong coding in Python and C++ . Deep understanding of autonomous decision-making, multi-agent coordination, and simulation frameworks.Mindset: Ability to move from research prototype to production-grade systemCommitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence.We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About the teamOpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and product direction.This group is an innovation loop within FDE. We sprint on a small number of platform bets at a time: identify high-signal problems emerging across deployments, build early versions quickly, validate them with design partners, and work with our core engineering and product counterparts to put successful bets on a scalable path. When a capability is ready to scale, we help transition ownership — and then move on to the next frontier.About the rolePlatform Incubation Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.You’ll join a small team working in pods against platform bets rather than a single long-running account. You’ll collaborate closely with customer-tagged FDEs and partner teams across engineering and product to: (1) incubate early versions, (2) validate them with design partners through short deployments or pilots, and (3) drive adoption by making the capability durable, usable, and ready to scale. You should expect to be customer-facing when it matters – pitching, rollout planning, debugging, and learning directly from what breaks in production – but your primary charter is to turn frontier signal into reusable platform capability.This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically <10%, with occasional spikes for key embeds or launches.In this role you willArchitect and build new platform capabilities: turn frontier customer signal into concrete designs, implementations, and APIs that become part of the OpenAI platform.Incubate platform bets end-to-end: take ambiguous problems, form a crisp hypothesis, ship an initial capability, and iterate quickly based on what breaks in real usage.Embed with design partners to learn fast: get close to production constraints, run deep technical discovery, and translate needs into product and platform requirements.Partner with customer-tagged FDEs in the field: deploy and debug together, capture repeatable patterns, and convert field learnings into platform improvements.Design and run pilot programs: define qualification criteria for early adopters, stand up internal/external alphas, and use pilots to harden both the platform and the rollout playbook.Collaborate as part of cross-functional platform teams: partner closely with core product and engineering counterparts, often as a single virtual team, to align on architecture and get to production together.Drive adoption outcomes: measure usage, identify blockers and failure modes, and prioritize the next platform increments that unlock repeatable value.You might thrive in this role if youBring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).Communicate clearly across engineering, product, go-to-market, and executive audiences, simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation.Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable product requirements and reusable platform capabilities, not one-off fixes or bespoke delivery work.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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About Terra AIWe are building the state-of-the-art AI platform for the discovery and development of clean energy and mineral resources. We bring the most advanced techniques in generative AI, foundation modeling, and autonomous decision optimization to tackle the most important problems in the geosciences. These systems can help more reliably identify critical resource deposits, more rapidly measure and characterize them, and design more efficient and sustainable production plans.We are backed by Khosla Ventures and other leading venture investors. We are now looking to grow our team from ~15 to ~30 by the end of the year to continue to mature our technology and support deployment with our world-class mineral and clean energy partners.Role descriptionIn the same way image generators have shown the remarkable ability to produce a diverse set of realistic pictures conditioned on a text prompt (and other inputs), we are developing a generative model that produces 3D geological models conditioned on geophysical surveys, bore hole measurements, and other forms of physical observation. The outputs of the generative model capture what we know and don’t know about the state of the subsurface, allowing explorers to make maximally informed decisions about how and where to explore for critical resources. We are looking for a talented deep learning engineer or scientist to lead the development of this model that will revolutionize decision making in the earth subsurface for a wide range of clean energy applications.Role ResponsibilitiesDesign, train, test, and iterate on diffusion models for 3D geological modelsDesign, train, test, and iterate on an approach to for conditioning generation on geophysical data and other observationsInform the generation of synthetic data to improve model performanceAdapt diffusion modeling approach to specific real-world projects in collaboration with project teams. QualificationsRequired Qualifications:Extensive PyTorch ExperienceDeep understanding of PyTorch, including writing custom modules, optimizing training, and debugging issues in large-scale models.Expertise in Developing Large Deep Learning Models from ScratchProven ability to design, implement, and train complex deep learning architectures from the ground up.Data Curation SkillsHands-on experience in creating, cleaning, and maintaining high-quality datasets tailored for machine learning applications.Strong Software Engineering and Design ExperienceProficient in software development best practices, including version control, testing, and code optimization.Familiarity with designing scalable and maintainable systems.Bonus points if you:Experience with Generative ModelsFamiliarity with generative architectures, particularly diffusion models, and an emphasis on posterior sampling methods.Knowledge of Transformer ArchitecturesExperience building and training transformers, especially in applications involving 3D data.Scaling Models Across Large GPU ClustersExpertise in parallelizing models across multiple GPUs and optimizing distributed training pipelines.Cloud Infrastructure ExpertiseExperience setting up, managing, and optimizing cloud environments for machine learning workloads, including provisioning resources and managing costs.

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About AdaptiveNVIDIA and OpenAI’s only AI cybersecurity investment.Adaptive is a cybersecurity startup on a mission to stop AI-powered cyberattacks. In December 2025, the company announced an $81M Series B led by NVIDIA and Bain Capital Ventures, with participation from Capital One Ventures, Citi Ventures, and continued support from Andreessen Horowitz (a16z), the OpenAI Startup Fund, and Abstract Ventures. The round marked NVIDIA’s first AI cybersecurity investment.Adaptive was founded by Brian Long and Andrew Jones, repeat entrepreneurs who have built and scaled category-defining companies. Brian and Andrew previously co-founded Attentive, which grew to more than $500M in annual revenue and a $10B+ valuation, and TapCommerce, which was acquired by Twitter. Together, they bring deep experience building high-growth, product-led businesses at massive scale as Adaptive builds the security layer for the AI era.Trusted by leading banks, technology companies, and healthcare organizations, Adaptive protects teams from emerging threats like deepfakes, smishing, and AI-powered voice scams. With rapid enterprise adoption and a $200B+ market ahead, the company is just getting started.RoleWe are seeking a Staff ML Engineer to define and build Adaptive's ML capabilities. Adaptive is an AI cybersecurity company whose products use LLMs and ML models to detect, classify, and respond to threats in real time. ML is central to the future of our products, and we need someone who can own the strategy, infrastructure, and execution for how we use it.We don't have dedicated ML infrastructure or an ML team today. You'll be building this from the ground up. You'll set the technical direction for how we use ML across the company, stand up the infrastructure, and do the hands-on work yourself.ResponsibilitiesDefine Adaptive's ML strategy: where ML should be applied across our products, what infrastructure we need, and how we should approach build vs. buy decisions.Design and build production ML systems end-to-end — data pipelines, model training, evaluation frameworks, and inference serving.Establish evaluation methodology. Define how we measure model quality, catch regressions, and make data-driven decisions about model changes.Own the strategy for getting the data you need, in the format you need it — what/how to label, how to build feedback loops, and how our models improve over time.Partner with product engineers to integrate ML into the product. You will write production code and work within our existing codebase.Over time, help build and lead the ML team as scope grows.Qualifications8+ years of experience building ML systems in production, ideally with experience standing up the ML function at an early stage startup or as the senior or lead ML person at a previous company.Strong software engineering fundamentals. You write production-quality code in modern languages (Python, Java, TypeScript) and work within large codebases.Experience with cloud ML infrastructure (AWS SageMaker, Bedrock, Modal, Baseten, or similar).Experience with common ML and data processing frameworks (PyTorch, Tensorflow, Spark)Comfortable working across the stack — infrastructure, backend services, and data systems.Track record of mentoring MLEs and other engineers with observable, clear improvements in those you've worked with.High autonomy. You'll have support and context from leadership, but you're expected to define the path forward and drive it.

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We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable. We’ve created our vehicle specifically for dense, complicated urban environments. Zoox is the only driving vehicle on the market with bidirectional driving capabilities and four-wheel steering, allowing us to maneuver through compact spaces and change directions without the need to reverse. The future is for riders! Our growing software engineering leadership team is searching for a Senior Manager of Perception. Our perception stack is responsible for building Zoox’s world-class 3D environment model from multi-modal sensor data. We create novel AI architectures that combine the latest academic results with many in-house innovations in creative ways. Our algorithms are relentlessly optimized and tuned to run efficiently and effectively on a wide variety of real-life data as well as in simulation. You will be responsible for leading high-impact Perception teams with their technical roadmap and milestone goals. You will be closely collaborating with other AI and SW leaders, simulation, and our systems design and mission assurance teams to deliver an exceptional dynamic objects perception system encompassing modalities such as vision, lidar, radar and long-wave IR across pipelines such as segmentation, detection, classification, fusion and tracking. You will lead a diverse, experienced team with a rapidly growing scope and responsibility while also working on some of the most complex problems in artificial intelligence, perception, and sensor fusion. In this role, you will:Build and lead a group of managers and engineers, and be responsible for the team’s roadmap, productivity, execution and impact within the company.Set the vision for, grow, and lead a team of talented software engineers in the overall planning, execution, and success of complex technical projects, while providing the team with technical leadership.Collaborate with engineers and leaders across a variety of teams to brainstorm and accelerate the development of perception capabilities.Provide clear summaries, progress, and recommendations to our executive leadership team.Establishing best practices and statistical rigor around data-driven decision-making.Stay on top of industry and academic trends in AI and perception, making sure Zoox remains at the cutting edge of both algorithms and their implementation at scale.QualificationsStrong understanding of computer vision systems and AI software stacks.5+ years of extensive leadership experience, leading teams of 20+10+ years of experience in computer vision, machine learning and related technologies.Strong leadership skills suitable for recruiting, leading, growing, and managing technical team members in solving a challenging problem, and building a critical component of a real-time system.Recent experience in implementing vision & perception algorithms.Expertise in implementing autonomy solutions and deploying real-world systems.Experience with recent AI approaches including E2E models for perception, transformers and sparse networks.Experience with sensor fusion and uncertainty modeling across multiple modalities.Strong presentation and communication skills.MSc or PhD in Robotics, Computer Science or related fields.Bonus QualificationsFamiliarity with perception of autonomous vehicles or similar robotsHands-on experience having deployed real products or platforms into the real world, and intimately understanding the challenges of working with complex systemsInvolvement in validation or evaluation of risk and/or safety-critical systemsKnowledge of GPU and/or TPU programming (CUDA, TensorRT, etc.) 277,000 - 389,000 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.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started. Role OverviewAs a Engineering Manager, Product at Harvey, you’ll play a pivotal role in shaping the foundation of our product platform while directly building user-facing features for some of the world’s leading law firms and enterprise customers. This team owns and operates the platform layer that enables secure, reliable, and flexible experiences for our customers including notifications, permissions and feature flag infrastructure. We also build enterprise-grade collaboration product experiences for law firms.You will design and own systems that not only serve as critical infrastructure for the rest of the company, but also directly impact how our users engage with Harvey’s AI-powered legal tools. This role is ideal for engineers who are excited by the opportunity to move between deep platform thinking and hands-on product iteration.This role is based in Toronto, Canada. We use a hybrid, 3+ days-per week in-person work model and offer relocation assistance to new employees.What You'll Do Own end-to-end delivery of core product initiatives, from technical design through execution and iteration, while directly managing a high-performing fullstack engineering team.Set technical direction for large-scale, AI-powered systems, including:Retrieval over petabyte-scale document collections.Product interfaces that enable organizations to collaborate with AI.Long-horizon (1000+ step) planning agents for mission-critical workflows.Government-grade security for highly sensitive data.Evaluation of LLMs across a 10k+ leaf taxonomy of tasks.Internet-scale data collection across 50+ jurisdictions.Translate product vision into architecture, making pragmatic tradeoffs that balance speed, quality, and long-term scalability in a fast-moving environment.Lead hands-on when it matters: contribute to design, code, and architecture reviews, and dive into implementation to unblock the team or tackle the hardest problems.Build and grow your team by hiring exceptional engineers, setting clear technical and behavioral standards, and investing in mentorship and career development.Partner deeply with Product, Design, and AI to identify high-leverage opportunities and ship highly intuitive, detail-oriented user experiences.Establish a strong engineering culture centered on simplicity, ownership, craftsmanship, and continuous improvement.Align execution with company goals, ensuring technical investments directly support product strategy and long-term impact.What You Have6+ years of experience as a product-focused fullstack or backend software engineer (post BS/MS), with a history of shipping real products to real users.2+ years of experience leading engineers, with clear ownership over both delivery and team health. Past management experience is a plus.A proven ability to design and operate backend platforms that support multiple product lines at scale.Strong experience with modern frontend frameworks (e.g. React) or backend systems (e.g. Python, Node, Go).Excellent technical judgment: you know when to move fast, when to invest, and when to simplify.A strong product instinct and attention to detail, with a track record of building intuitive, high-quality user experiences.Demonstrated success building, motivating, and retaining high-performing teams in high-growth environments.Solid computer science fundamentals and strong programming skills.Grit and ownership mindset — you’re comfortable operating in ambiguity and taking responsibility for outcomes.Bonus: experience with AI-powered applications, large-scale data systems, LLM evaluation, or complex internal platforms.What We OfferBe part of building something special as a founding member of our Toronto teamStructured hybrid working arrangement: 3 days in our Toronto office, 2 days working from home We are an AI company and we use AI to improve all of our processes, including in the recruitment process. Whilst we do use AI to help improve efficiency in our recruitment process, we do not rely on AI to make any automated decisions and ensure that a human reviews AI output.#LI-KT1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai