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🎨 OpusClip is the world's No.1 AI video agent, built for authenticity on social media.We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used OpusClip to enhance their social presence. We have raised $50 million in total funding and are fortunate to have some of the most supportive investors, including SoftBank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (SaaStr), Samsung Next, GTMfund, Alumni Ventures, and many more. Check out our latest coverage by Business Insider featuring our product and funding milestones, and our recognition as one of The Information's 50 Most Promising Startups in 2024. Headquartered in Palo Alto, we are a team of 100 passionate and experienced AI enthusiasts and video experts, driven by our core values: Be a Champion Team Prioritize Ruthlessly Ship fast, Quality Follows Obsess over customers Be a part of this exciting journey with us!The RoleOpus Clip is redefining the architecture of digital storytelling. We are seeking a Senior Product Manager who operates at the intersection of elite design intuition and multimodal AI. This is not a role for a process-oriented administrator, but a visionary generalist who possesses a "design-first" soul and a "code-first" execution style. You won't just manage a roadmap; you will architect the future of how the world creates and consumes video.The MandateArchitect Product Artistry: Bridge the gap between complex AI research and seamless user experiences. You will transform raw model capabilities and complex workflows into polished products that feel like magic to millions of creators.Guardian of Taste: Act as the final filter for aesthetic quality. You will ensure every feature meets an uncompromising standard for rhythm, composition, and visual harmony.Rapid Prototyping: Lead through execution by building functional proofs-of-concept. You will work directly with APIs and codebase to validate hypotheses before they move to full-scale engineering.Strategic Market Pioneering: Identify latent creator needs and competitive gaps long before they become industry consensus. You will prioritize bold, high-impact bets over safe, incremental iterations.The ProfileThe Hybrid Architect: 4–8 years of experience in product leadership, with a portfolio that proves you can build products that are as beautiful as they are functional.Multimodal Practitioner: You are proficient in the nuances of video, audio, and language models. You are comfortable "vibing" code and navigating a repository.Founder-Level Agency: You possess the "street-smart" intuition required to thrive in a high-growth environment. You are a self-starter who treats the product like your own company.Creator-Centric Soul: You likely have a background as an artist, designer, or filmmaker. You have a visceral empathy for the creative process and an obsession with empowering creators through technology.EEOOpusClip is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics. OpusClip considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Opus Clip is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Chime, Oura Health, 1-800-FLOWERS, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just get it done, Invent what customers want, Winner’s mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.About the RoleAs a Staff Voice Research Engineer, you’ll lead the development of the models and algorithms that power Decagon’s industry-leading, real-time voice agents, and drive them all the way into production. You’ll own multi-quarter initiatives that advance speech understanding, naturalness, turn-taking, and resilience in real-world conditions. You’ll design and implement frontier approaches for training, evaluation, and orchestration across the voice agent.We’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.In this role, you willLead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completionBuild and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experiencePartner with platform and product engineers to integrate new models into production systemsBreak down ambiguous research ideas into clear, iterative milestones and roadmaps.Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineeringYour background looks something like this8+ years of experience in AI/ML engineering or research.Prior experience post-training and deploying LLMs in production environments.Fluency in Python and modern ML tooling (training, evaluation, data pipelines)Track record of taking research ideas from prototype → reliable, measurable production impactAbility to define a roadmap, break ambiguity into milestones, and lead cross-functional executionBenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$350K – $475K + Offers Equity

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Chime, Oura Health, 1-800-FLOWERS, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just get it done, Invent what customers want, Winner’s mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.About the RoleAs a Staff Research Engineer, you’ll be responsible for building industry-leading conversational AI models that power Decagon’s agent, and taking them all the way from idea to production. You’ll own multi-quarter initiatives that push the agent’s reliability, capability, and efficiency forward, and you’ll design and implement frontier approaches for training, evaluation, and orchestration across the system.We’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.In this role, you willLead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completionBuild and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experiencePartner with platform and product engineers to integrate new models into production systemsBreak down ambiguous research ideas into clear, iterative milestones and roadmaps.Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineeringYour background looks something like this8+ years of experience in AI/ML engineering or research.Prior experience post-training and deploying LLMs in production environments.Fluency in Python and modern ML tooling (training, evaluation, data pipelines)Track record of taking research ideas from prototype → reliable, measurable production impactAbility to define a roadmap, break ambiguity into milestones, and lead cross-functional executionBenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation$350K – $475K + Offers Equity

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE 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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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.Job SummaryAs a Senior Software Engineer on the Pilots team within the Perception organization, you will be responsible for developing prototypes for forthcoming pilots, aligning with Hayden’s mission and long-term roadmap for business expansion.This team investigates novel use cases, vehicles, and deployment environments, expeditiously translating preliminary concepts into functional prototypes. You will construct comprehensive end-to-end perception and robotics systems designed to operate on real-world hardware and capable of scaling into Hayden’s core product platform.This is a C++ software engineering generalist position emphasizing robotics and systems expertise. You will function with a substantial degree of ownership, navigating complexity to meticulously design, implement, and fortify solutions that judiciously balance rapid experimentation with sustained maintainability. Key Responsibilities:Deliver robust, thoroughly tested, and maintainable C++ code tailored for edge and robotics platforms.Design, implement, and take ownership of prototype perception systems with the potential to transition into production-grade solutions.Construct and iteratively refine real-time perception pipelines, encompassing detection, tracking, and sensor fusion methodologies.Adapt, refine, and integrate Machine Learning (ML) and Computer Vision (CV) models, including leveraging open-source solutions, for novel, Hayden-specific applications.Drive technical decision-making in ambiguous problem spaces, effectively balancing the speed required for prototyping with the requirements for production readiness.Collaborate closely with the Product team and cross-functional Engineering departments.Contribute to shared infrastructure, tooling, and architectural patterns as pilot initiatives mature into foundational products.Required Qualifications:Master's degree in Computer Science, Electrical Engineering, Robotics, or a closely related discipline. A PhD is considered advantageous.5-8 years of relevant experience in building and deploying perception systems; experience in automotive or robotics domains is a plus.Substantial background in a minimum of one of the following domains: robotics, state estimation, computer vision, or applied machine learning.Senior-level industrial experience in the delivery of intricate, production-grade software systems.Demonstrated proficiency in modern C++, coupled with experience in real-time systems.Experience in the construction and ownership of end-to-end systems, rather than merely isolated components.Capability to operate effectively in ambiguous and rapidly evolving environments.Proven capacity to collaborate constructively within a developing engineering organization.

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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 RoleWe are looking for a Computer Vision Engineer to contribute to the development of the front-end of our visual inertial odometry (VIO) algorithmic stack.ResponsibilitiesVIO Front-end Algorithm development:Matching between frames and stereo pairsCalibration of cameras intrinsic and extrinsic parametersDetection of obstructionImplementation and optimization of the algorithmic stack for our embedded platformsTesting, Validation & Monitoring: algorithms testing in simulation and real-world environments, development of inspection and monitoring tools..Cross-Team Collaboration: Work closely with system engineers, optical engineers, software engineers. Communicate findings effectively to stakeholders.Candidate RequirementsEducational Background: Master’s degree in Robotics, Physics, Computer Science or related field, PhD is a plusTechnical Expertise: Strong mathematical foundations, coding skills in both Python and C++Hands-on VIO project experience. Experience with VIO on industrial products is a huge plus.Passion for Computer Vision and RoboticsStrong Communication & Teamwork: Ability to collaborate effectively with diverse teamsCommitment: 100% dedication to Harmattan’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 TeamThe Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers.Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale.We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform.About the RoleAs a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale.You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads.This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging.In This Role, You WillDesign and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobsDevelop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behaviorImprove observability, reliability, and performance across OpenAI’s training platformDebug and resolve issues in complex, high-throughput distributed systemsCollaborate with systems, infrastructure, and research teams to evolve platform capabilitiesExtend and adapt failure detection systems or tracing systems to support new training paradigms and workloadsYou Might Thrive in This Role If YouCare deeply about performance, stability, and observability in distributed systemsEnjoy finding and fixing issues in large-scale systems and automating operational workflowsHave experience writing low-level software where system details matterUnderstand hardware, operating systems, networking, concurrency, and distributed systemsHave a background in high-performance computing or low-level systems engineeringAre excited to work on critical infrastructure that powers frontier AI researchAbout 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 the TeamThe Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers.Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale.We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform.About the RoleAs a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale.You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads.This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging.In This Role, You WillDesign and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobsDevelop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behaviorImprove observability, reliability, and performance across OpenAI’s training platformDebug and resolve issues in complex, high-throughput distributed systemsCollaborate with systems, infrastructure, and research teams to evolve platform capabilitiesExtend and adapt failure detection systems or tracing systems to support new training paradigms and workloadsYou Might Thrive in This Role If YouCare deeply about performance, stability, and observability in distributed systemsEnjoy finding and fixing issues in large-scale systems and automating operational workflowsHave experience writing low-level software where system details matterUnderstand hardware, operating systems, networking, concurrency, and distributed systemsHave a background in high-performance computing or low-level systems engineeringAre excited to work on critical infrastructure that powers frontier AI researchAbout 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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Netic is the AI revenue engine for essential services who are the backbone of the American economy. With $43M in funding from Founders Fund, Greylock, Hanabi, and Dylan Field who led our Series B, we helped our customers book hundreds of thousands of jobs across services industries in North America. There are now companies operating entirely AI-first on Netic. You’ll join our team with relentless builders from Scale, Databricks, HRT, Meta, MIT, Stanford, and Harvard in bringing frontier AI to the physical economy, where the problems are hard, the data is complex, and the impact is immediate and tangible.As a Founding Platform Engineer, you will own the semantic layer that powers our system of record and enables compounding products across the company. What makes this role uniquely rare at Netic is the scope and shape of the platform we are building. From day one, our system of record has to work across industries, geographies, and regulatory environments. That requires a platform that is highly customizable to support different workflows and business rules, while still being tractable enough that engineers can understand, debug, and operate it in production.This platform directly determines how dynamic workflows are built, packaged, and delivered to customers. The abstractions you create will influence how quickly we can launch new products, expand into new verticals, and respond to real world edge cases without sacrificing reliability. If you are excited to design foundational systems where flexibility, correctness, and developer ergonomics all matter, this is an opportunity to build a durable, company defining platform.What You’ll DoBuild the Semantic Layer Design and own the semantic layer that powers our system-of-record flywheel. This layer is the foundation for how data, state, and meaning flow through the company, enabling compounding AI products across teams. Create Internal Platforms with Leverage Build primitives, abstractions, and APIs that product teams use as building blocks. Your success is measured by how easily other engineers can ship powerful AI-driven features on top of your work. Treat Product Teams as Customers Partner closely with internal product and engineering teams to understand their needs, eliminate friction, and design systems that are intuitive, well-documented, and hard to misuse. Architect for Multiple Data & Request Topologies Design systems that span data warehouses, OLTP databases, streaming systems, and vector stores. Make intentional tradeoffs based on latency, throughput, consistency, and access patterns. Set Platform Direction Work with leadership to define the long-term platform architecture, including build-vs-buy decisions, evolution of the semantic layer, and how the system scales as product surface area grows. What You’ll BringPlatform & Systems Experience 5+ years building and operating distributed systems, ideally with experience owning a platform or core abstraction used by multiple teams. Strong Data Systems Background Deep understanding of data warehouses, transactional databases, and other storage systems, including how to model data for different access patterns and workloads. Semantic & Abstraction Thinking Ability to design schemas, contracts, and semantic models that remain stable over time while supporting rapid product iteration. Operational Rigor Experience with observability, migrations, backfills, incident response, and running high-uptime systems that are hard to unwind once in production. Ownership Mentality You take responsibility for long-term outcomes, not just shipping code. You think in terms of flywheels, leverage, and second-order effects.We believe fulfillment comes from producing your best work with the smartest people together in one room. All roles are in person, in SF (our office is in Jackson Square). What brings us together is our commitment to:Live to buildRun through walls and winObsess over customers in each line of codeLose sleep over the "almost perfect"Show internal locus of controlPrioritize finesse: refinement of first principles thinking, execution, and craftsmanshipWe are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

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About Liquid AISpun out of MIT CSAIL, we build AI systems that run where others stall: on CPUs, with low latency, minimal memory, and maximum reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.The OpportunityThis is a rare chance to sit at the intersection of frontier foundation models and real-world deployment. You’ll own applied post-training work end-to-end for some of the world’s largest enterprises, while still contributing directly to Liquid’s core model development. Unlike most roles that force a trade-off between customer impact and foundational work, this role gives you both: deep ownership over how models are adapted, evaluated, and shipped, and a direct line into the evolution of Liquid’s post-training stack. If you care about data quality, evaluation, and making models actually work in production, this is a chance to shape how applied AI is done at a foundation-model company.What We're Looking ForWe need someone who:Takes ownership: Owns post-training projects end-to-end, from customer requirements through delivery and evaluation.Thinks end-to-end: Can reason across data generation, training, alignment, and evaluation as a single system.Is pragmatic: Optimises for model quality and customer outcomes over publications or theory.Communicates clearly: Can translate between customer needs and internal technical teams, and push back when needed. The WorkAct as the technical owner for enterprise customer post-training engagements.Translate customer requirements into concrete post-training specifications and workflows.Design and execute data generation, filtering, and quality assessment processes.Run supervised fine-tuning, preference alignment, and reinforcement learning workflows.Design task-specific evaluations, interpret results, and feed learnings back into core post-training pipelines.Desired ExperienceMust-have:Hands-on experience with data generation and evaluation for LLM post-training.Experience training or fine-tuning models using SFT, preference alignment, and/or RL.Strong intuition for data quality and evaluation design.Familiarity with alignment or RL techniques beyond basic supervised fine-tuning.Nice-to-have:Experience contributing to shared or general-purpose post-training infrastructure.Prior exposure to customer-facing or applied ML delivery environments.Familiarity with alignment or RL techniques beyond basic supervised fine-tuning.What Success Looks Like (Year One)Independently owns and delivers enterprise post-training projects with minimal oversight.Is trusted by customers as the technical owner, demonstrating strong judgment and delivery quality.Has made durable contributions to Liquid’s general-purpose post-training pipelines by feeding applied learnings back into baseline model development.What We OfferCompensation: Competitive base salary with equity in a unicorn-stage companyHealth: We pay 100% of medical, dental, and vision premiums for employees and dependentsFinancial: 401(k) matching up to 4% of base payTime Off: Unlimited PTO plus company-wide Refill Days throughout the year

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About Meeno Backed by Sequoia Capital, AI Fund & NEA, and founded by the former CEO of Tinder, Meeno helps people build real-world social courage through voice-based practice: 1-minute scenes, instant scoring, and personalized feedback. Not a dating app. Not a companion. Not therapy. IRL reps to help Gen Z meet people IRL.What You'll DoOwn the technical foundation of Meeno end-to-end: Web + mobile + backend + data + experimentationCo-design product vision in close partnership with Meeno’s team:Renate Nyborg, founder/CEO (former Tinder CEO, ex Apple/Headspace)Josh Knox, product lead (founder of Outright, brand and content expert)Andrew Ng, Chairman (AI Fund, founder of Coursera/Google Brain)Build core AI product primitives:Voice capture/playbackLow-latency interactionsScene framework (content + branching + scoring hooks)Feedback loops and user progressionPersonalizationArchitect for speed + iteration (weekly experiments, not quarterly releases).Set the engineering bar:Quality, reliability, security/privacy, and shipping culture.Hire and mentor engineers as we scale:Focus on quality over quantity, leveraging AI and talent to scale while staying lean.What We're Looking ForStrong builder who has shipped consumer products.Comfortable with ambiguity and moving fast without breaking the soul of the product.Product taste: you care about “feel,” not just functionality.Excited by voice, interaction design, and behavior change.Can operate like a founder: make tradeoffs, set direction, ship.Green flags (not requirements)Hyped about social connection, empathy for Gen Z loneliness.Early adopter of AI-driven development.Hungry for rapid career progression and societal impact.Experience with audio/voice pipelines, realtime systems, mobile performance.History of building unconventional projects (creative tech, experiments, indie builds).Interest in human behavior, social dynamics, and product psychology.You won't pass the vibe check if...You are not passionate about our mission.You only want to manage, not build.You need perfect specs to move.You optimize for process over product feel.You are not fun.What success looks like (first 6 months)Meeno has a stable foundation, and we can run rapid experiments.Our product feels fast, human, and culturally sharp.We have a pipeline of world-class engineering talent.We are well-positioned to raise Series A with clear signal on north star metrics.We are having fun. 180,000 - 220,000 a year

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About the TeamOpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI.About the RoleWe’re looking for a RTL Engineer to design and implement key compute, memory, and interconnect components for our custom AI accelerator. You’ll work closely with architecture, verification, physical design, and ML engineers to translate AI workloads into efficient hardware structures. This is a hands-on design role with significant ownership across definition, modeling, and implementation.This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.ResponsibilitiesProduce clean, production-quality microarchitecture and RTL for major accelerator subsystemsContribute to architectural studies including performance modeling and feasibility analysis.Collaborate with software, simulator, and compiler teams to ensure hardware/software co-design and workload fit.Partner with DV and PD to ensure functional correctness, timing closure, area/power targets, and clean integration.Build and review performance and functional models to validate design intent.Participate in design reviews, documentation, and bring-up support across the full silicon lifecycle.You Might Thrive In This Role If You Have:Graduate-level research or industry experience in computer architecture, AI/ML hardware–software co-design, including workload analysis, dataflow mapping, or accelerator algorithm optimization.Expertise writing production-quality RTL in Verilog/SystemVerilog, with a track record of delivering complex blocks to tape-out.Experience developing hardware design models or architectural simulators, ideally for AI/ML or high-performance compute systems.Familiarity with industry-standard design tools (lint, CDC/RDC, synthesis, STA) and methodologies.Ability to work cross-functionally with architecture, ML systems, compilers, and verification teams.Strong problem-solving skills and ability to think across abstraction layers, from algorithms to circuits.Passion for building industry-leading massive-scale hardware systems.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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The Perception team at Zoox is fundamental to our autonomous vehicle technology, creating the understanding of the world for our self-driving robots. We enable safe and efficient navigation in complex environments through sophisticated detection, classification, and tracking systems. As a software engineer on the perception mapping team, you will be a key contributor to Zoox’s online mapping initiative. You will design, train, validate, and integrate into the stack ML models that detect semantic map elements in the world. Your work will touch on all aspects of ML development, including data gathering, labeling, training, validation, and onboard integration. Your work will enable important milestones to scaling and autonomy capabilities and will be critical to the success of Zoox.In this role, you will: Curate, validate, and label datasets for model training and validationResearch, implement, and train ML models to perform semantic map element detectionClosely collaborate with validation teams to formulate and execute model validation pipelinesIntegrate models into the greater onboard autonomy system within compute budgetsBe a technical leader on the team, maintaining coding and ML development best practices and contributing to architectural decisionsQualifications:MS or PhD or equivalent experience (5+ years) in Computer Science or related fieldExperience in computer vision or roboticsExperience with training and deploying deep learning modelsExperience with with Python libraries (pytorch, numpy)Bonus Qualifications: Experience with C++Experience with CUDA and/or GPU programmingExperience with mapping related ML techniques 189,000 - 227,000 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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As a Member of Technical Staff on Applied AI, you will:Productionize frontier AI models to solve complex real-world problems.Collaborate closely with researchers and other teammates on the latest advancements in AI and ML.Work closely with our customers to integrate our models into their technology stack.Make direct business impact with a high level of product ownership.Be a founding member of a fast-growing team and wear many hats.You may be a good fit, if you have:An obsession with customers and a passion for solving practical (but sometimes ambiguous) real-world problems.Experience as a machine learning engineer, ideally working on AI products for external customers.Background as a technical founder or in a similar capacity.Practical experience working with transformer models and LLMs. An exceptional ability to communicate and work effectively with cross-functional teams.Track records of owning problems end-to-end, and can learn fast and pick up new knowledge to get the job done. A kind and collaborative nature and work style.Reka's MissionReka's mission is to build useful multimodal artificial intelligence and use it to empower organisations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade.Why Reka?An Elite Team: Collaborate with top-tier engineers, researchers, operators from renowned organizations like Google DeepMind and Facebook AI Research (FAIR) and successful startups, driving innovation in cutting-edge AI technology.Massive Market Opportunity: Be part of a rapidly growing industry poised to transform multiple sectors globally, offering the chance to make a significant impact.Mission-Driven Environment: Work alongside a collaborative, mission-focused team dedicated to advancing AI for meaningful applications.Inclusive and Open Culture: Thrive in an open and inclusive work environment that values diverse perspectives and fosters creativity.Generous Benefits: Enjoy 5 weeks of paid leave to recharge, comprehensive healthcare benefits including vision and dental, and additional perks that support your well-being.Visa Support: We provide visa assistance, including H1B and OPT transfers, for US employees to ensure a smooth transition and support your career with us.

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About the teamThe Codex Deployment Engineering team helps customers adopt OpenAI's coding tools throughout their software development lifecycle. We act as trusted technical partners, guiding engineering teams as they integrate Codex into their projects and workflows. Our customers span digital-native companies to global enterprises, and we work side-by-side to accelerate how they plan, build, and deliver software.About the RoleWe are seeking a technically deep, creativity-driven AI Deployment Engineer who is already a power user of AI coding tools and passionate about pushing the boundaries of developer productivity. You will partner directly with engineering leaders and hands-on builders to design, validate, and scale advanced AI workflows, often using Codex to prototype and build the very demos, integrations, and automations customers ultimately adopt.This is a highly cross-functional role that blends technical architecture, product strategy, and customer-facing leadership. You’ll work closely with Sales, Solutions Engineering, Product, Applied Engineering, and the broader Codex organization to advocate for customer needs, shape product direction, and accelerate the successful deployment of intelligent coding systems across some of the world’s most influential companies.In this role, you will:Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows.Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout.Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process.Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely.Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to help the broader developer community accelerate their work with Codex.Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams.Influence customer strategy and decision-making by framing how AI coding tools fit into their SDLC, technical roadmap, and organizational workflows.Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.You’ll thrive in this role if you:Have 5+ years of technical consulting, post-sales engineering, solutions architecture, or similar experience working directly with customers.Are an active power user of AI coding tools and have deeply customized your own developer workflow; you have a point of view on what makes engineers more productive.Enjoy building scrappy, high-signal demos, integrations, and prototypes that clearly articulate what Codex can enable, often using Codex to accelerate your own development process.Have experience delivering large, high-impact workshops or technical training to engineering teams and know how to craft sessions that are engaging, hands-on, and outcomes-driven.Have contributed technical guides, patterns, or examples publicly and care about clarity, pedagogy, and community impact.Communicate complex technical concepts in clear, persuasive written and verbal form especially when helping customers make strategic decisions about where and how to apply AI.Are excited by ambiguous, rapidly evolving problem spaces and enjoy iterating toward novel solutions hand-in-hand with customers.Care about customer success, reliability, safety, and operational excellence as much as you care about technical ingenuity.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 ElicitElicit is an AI research platform that uses language models to help researchers figure out what's true and make better decisions, starting with common research tasks like literature review.What we're aiming for:Elicit radically increases the amount of good reasoning in the world.For experts, Elicit pushes the frontier forward.For non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit.Elicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes. This expands our collective understanding of safe AGI architectures.Visit our Twitter to learn more about how Elicit is helping researchers and making progress on our mission.The mission of Elicit evalsSome orgs build evals to warn us about dangerous capabilities. Others build evals to understand trends and predict future developments. Yet others build evals to hill-climb towards models that users will like more.At Elicit, we're focused on something different—we want to understand, and hill-climb towards, models that help us make better decisions.This is tougher than "what will users like better"—it's hard to evaluate decision support, and users' knee-jerk reactions may not align with what actually helps for decision-making. Because it's hard, and because the sales pitch is more complicated, there aren't many doing this well. If we nail this, we have a unique opportunity to push AI toward helping us make better decisions, both within Elicit and beyond.Why we're hiring for this roleWe need someone to own the technical foundation of our auto-evaluation systems. Our evals are currently much slower than they need to be, and our interfaces aren't optimized for the diverse set of people who need to use them—ML engineers iterating on models, product managers monitoring quality, and customers assessing trust in results.The right person for this role won't just build infrastructure. You'll think deeply about what it actually means for Elicit to help with decision-making in pharma and encode that understanding into our evaluation systems.What you'll ownThe core auto-eval platformYou'll build a comprehensive system that runs fast, is easy to use, and supports quickly building new evals:Speed: You’ll build a lightning-fast basic evals infrastructure that schedules tasks to introduce practically no latency; and then you’ll figure out clever ways to solve the fundamental sources of latency (building a version of Elicit, running it on a query, and evaluating it using LMs)Interfaces: ML engineers need evals to kick off automatically on relevant commits, with results they can see at a glance and drill into. Product managers need dashboards showing performance over time and what's going wrong in production.Architecture: Your code must be well-architected so other team members and ML engineers can understand and build on it. An engineer starting on a new feature should be able to quickly add examples and run an eval.Ensuring evaluations are accurate and reliableWe need to evaluate how well Elicit actually helps with decision-making in pharma, not just measure what's easy to measure. This requires encoding real knowledge about how pharma customers make decisions (for example, choosing appropriate gold standards).You'll provide appropriate statistical tests and confidence intervals so we can trust our results.A month in your lifeIn a typical month, expect to spend:60% working on the core eval platform15% working closely with the evals team to build and improve specific evals (e.g., an eval of our paper search within our systematic review flow)10% mentoring our evals engineering internThe rest on learning how people interact with the eval system so you can make it work better for them, and understanding what our users want from Elicit so evals measure what mattersWhat you bring to the roleRequirementsAt least 3 years of experience as a professional software engineer, with demonstrated experience building complex backend systems (e.g., backend for a complex website, data pipelines, etc.)Aptitude and interest in evaluating how Elicit helps with pharma decision-making. There's no particular experience you must have, but we'll evaluate your aptitude.Will make you more competitive for the roleKnowledge of statistics (for e.g. calculating power and credence intervals for evals)Experience with advanced Python (asyncio/trio and parallel processing strategies)Front-end experience and strong UX sensibility (you'll be building dashboards). TypeScript experience is a plus.Experience building developer tools (ML engineers are one of your most important clients)Previous experience as a data engineer or working on AI infrastructureKnowledge of pharma/biomedExperience evaluating ML systemsExperience building language-model-based systems (helps with understanding Elicit and how to evaluate it)This is a diverse list of nice-to-haves. We expect the candidate we select to have some, but not all, of these. Other team members can fill in for skills you lack.Location and travelWe have a lovely office in Oakland, CA, but we’re flexible about where you work. You’re welcome to work remotely, from our Oakland headquarters, or in a hybrid setup. The only in-person requirement is attending our quarterly team retreats, typically held on the west coast. Compensation, benefits, and perksIn addition to working on important problems as part of a productive and positive team, we also offer great benefits (with some variation based on location):Flexible work environment: work from our office in Oakland or remotely with time zone overlap (between GMT and GMT-8), as long as you can travel for in-person retreats and coworking eventsFully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your familyFlexible vacation policy, with a minimum recommendation of 20 days/year + company holidays401K with a 6% employer matchA new Mac + $1,000 budget to set up your workstation or home office in your first year, then $500 every year thereafter$1,000 quarterly AI Experimentation & Learning budget, so you can freely experiment with new AI tools, take courses, purchase educational resources, or attend AI-focused conferences and eventsA team administrative assistant who can help you with personal and work tasksFor all roles at Elicit, we use a data-backed compensation framework to keep salaries market-competitive, equitable, and simple to understand. For this role, we target starting ranges of:Career (L3): $140-170k + equitySenior (L4): $165-200k + equity

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LandingAI is a leader in Agentic Document Intelligence. Our flagship solution, Agentic Document Extraction (ADE), replaces traditional OCR with layout-aware AI system that parses complex documents without the need for rigid templates. By providing visual grounding for full auditability, ADE enables high-stakes industries like financial services and healthcare to extract valuable data and to automate critical workflows with unmatched accuracy. In addition to document intelligence, we offer the LandingLens™ platform for vision-AI anchored computer vision applications including inspection, defect detection and robotics. About the Role: As a Software Engineer at LandingAI, you will build and maintain core web applications and services that power our AI-driven products. While you will not be responsible for developing machine learning models, you will work very closely with ML engineers to integrate ML capabilities into scalable, reliable, and user-friendly software systems. This role sits at the intersection of software engineering and applied AI, enabling ML innovations to reach customers through high-quality products.Key Responsibilities:Design, develop, and maintain web applications and backend services that integrate ML-powered features.Collaborate closely with Machine Learning Engineers and Product Managers to understand ML system requirements and translate them into robust software solutions.Build reliable, scalable, and low-latency services that support ML inference, data workflows, and AI-driven user experiences.Use LLMs to build scalable and reliable AI agents.Own the full software development lifecycle: design, implementation, testing, deployment, monitoring, and maintenance.Ensure high standards for code quality, testing, observability, and operational excellence.Troubleshoot production issues and participate in on-call or support rotations when needed.Mentor junior engineers and contribute to technical best practices across teams.Act as a strong cross-functional partner between product, engineering, and ML teams.Required Qualifications:Minimum of 5 years of professional experience in software engineering.Advanced skills in Python, web backend development, and building AI agents.Knowledge of containerization tools (Docker, Kubernetes) or cloud platforms (AWS, GCP).In-depth understanding of web application architecture and API design principles.Proven experience integrating with external services or intricate backend systems.Experience working with LLMs to develop AI agents that are scalable and reliable.Experience evaluating and benchmarking AI products.Demonstrated ability to work autonomously, showing high ownership and accountability.Excellent communication skills and experience collaborating effectively with diverse, cross-functional teams.Flexibility to adjust working hours to accommodate the needs of a global team.Experience using AI Coding Agents like Claude Code to develop reliable, scalable and high quality code.Valuable / Bonus Qualifications:Experience with ML frameworks like PyTorch.Experience with serving ML models and LLMs (vLLM).Experience collaborating with Machine Learning (ML) or data teams.Familiarity with ML concepts, including inference, model serving, latency considerations, and data pipelines.Experience utilizing PostgreSQL, Object-Relational Mappers (ORMs), ETL pipelines.Experience developing developer-facing tools or internal platform solutions.LandingAI Benefits: Stock Options – We want you to share in our success with equity grants.Comprehensive Healthcare – Medical, dental, and vision coverage for you and your dependents.*Wellness Stipend – Support for your health and well-being, whether it’s fitness programs or self-care.*Lifelong Learning – An education stipend to help you grow and keep learning.Generous PTO – We know life happens outside of work, and we want you to enjoy it.*Global Team & Fun Events – Work with amazing colleagues across North America, Latin America, and Asia, and connect through virtual and in-person events.*Benefits may vary based on your country of employment. We deeply value true leadership, ownership, and an entrepreneurial mindset. We appreciate people who take pride in their work, follow through on commitments, and turn ideas into results.If this sounds like you, then you’ll feel right at home with us — and we’d love to connect.

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About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society.Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About The Job The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. However, the AI graveyard is full of great ideas nobody could measure or prototypes that never made it to production. As a first Evaluation Engineer, you'll design the methodology, build the infrastructure, and define what "ready for production" means across verticals and use cases. You will design and implement evaluation systems that help our customers understand model performance across their specific use cases, build robust evaluation infrastructure, and work closely with both research and customer-facing teams. Research builds evals for frontier capabilities but customers don't care about MMLU scores. We need in Applied AI evals and frameworks for customer reality domain-specific, risk-aware, production-grade. The kind that tell you whether your medical summarization model will hallucinate drug interactions, or whether your legal assistant will invent case citations. This role sits at the intersection of research, engineering, and solutions, you will play a critical cross role in measuring, understanding, and improving the capabilities of our models for our enterprise customers. What you will do - Design and implement comprehensive evaluation frameworks to measure LLM capabilities across diverse customer use cases, including text generation, reasoning, code, and domain-specific applications- Build scalable evaluation infrastructure and pipelines that enable rapid, reproducible assessment of model performance- Develop novel evaluation methodologies to assess emerging capabilities or verticalized use cases (cybersecurity, finance, healthcare, etc.) and enable the Solutions (Deployment Strategist and Applied AI) on these topics.- Create custom evaluation suites tailored to enterprise customers' specific needs, working closely with them to understand their requirements and success criteria- Collaborate with research teams to translate evaluation insights into model improvements and training decisions- Partner with product teams to continuously improve our evaluation tooling based on customer feedback How We Work in Applied AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it- Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.- Always ask why. The best solutions come from deep understanding, not from copying what worked before- We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards.- We embrace an unstructured environment and find joy in it. About you - You are fluent in English- 3+ years of experience in ML evaluation, benchmarking for LLM or agentic systems- You have proven experience in AI or machine learning product implementation with APIs, back-end- You have deep understanding of concepts and algorithms underlying machine learning and LLMs- You have strong technical coding skills in Python- You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: - Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation- Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager- Experience with ML frameworks (PyTorch, HuggingFace Transformers) Benefits 🏝️ PTO: The CDI contract will be a "Forfait 218 jours", corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours⚕️ Health : Full health insurance coverage for you and your family🚗 Transportation : We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling.🥕 Food : Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company🏀 Sport : Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)🐤 Parental policy : 4 additional weeks for parents on top of what is offered by the French state.

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About the role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll drive end-to-end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting-edge research into deployable, high-impact solutions. What you’ll do Translate research → product: work with client side researchers on post-training, evals, safety/alignment and build the primitives, data, and tooling they need. Partner deeply with core customers and frontier labs: work hands-on with leading AI teams and frontier research labs to tackle hard, open-ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post-training, evaluation, and safety work into well-defined statements of work and execution plans. Translate research into production impact: collaborate with customer-side researchers on post-training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice. Own the end-to-end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade-offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings. Lead complex, high-stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes. Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production-grade results for demanding customers. Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts. You have Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high-stakes, customer-facing environments. Hands-on experience with model improvement workflows: demonstrated experience with post-training techniques, evaluation design, benchmarking, and model quality iteration. Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models. Strong technical fluency: you can read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Bias to action: you ship, learn, and iterate. How you’ll work Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: expect regular customer time and research leads; light travel as needed. What success looks like Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$201,600—$241,920 USDPLEASE 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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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 RoleWe are looking for a Computer Vision Engineer to join our Machine Learning and Computer Vision team. This role is crucial for developing core technical components across various robotics/aerospace projects.ResponsibilitiesResearch & Data Preparation: Conduct research on state-of-the-art Computer Vision methodologies. Participate in the creation and curation of training and validation datasets. Perform statistical analyses and develop visualization tools to ensure data quality.Algorithm Development & Optimization: Build and refine training pipelines and metrics to enhance model performance.Develop and optimize Computer Vision algorithms for multiple robotics/aerospace projects.Deployment & Integration: Implement ML/CV models into production-ready environments. Ensure seamless integration with Harmattan AI’s systems and conduct rigorous code reviews.Validation & Monitoring: Test algorithms in real-world environments and develop monitoring tools. Track model performance and continuously improve deployed solutions.Cross-Team Collaboration: Work closely with software and simulation teams to align development with system requirements. Communicate findings effectively to stakeholders.Candidate RequirementsEducational Background: A degree from a top-tier engineering school or university (Master’s degree in Computer Science or related field, PhD is a plus)Technical Expertise: Strong mathematical foundations, coding skills (Python, C++ is a plus) and hands-on ML/CV project experience. Experience in top AI companies is a huge plus.Passion for ML: Enthusiasm for Machine Learning and Computer Vision. Strong Communication & Teamwork: Ability to collaborate effectively with diverse teamsCommitment: 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.