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Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system. Responsibilities Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration Requirements Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems Bonus Qualifications Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.) The US base salary range for this full-time position is between $150,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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About the teamOpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.About the roleWe are hiring a Forward Deployed Engineer (FDE) to lead end-to-end deployments of our models inside life sciences organizations and research institutions, from early R&D through clinical and operational workflows. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams.You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams.This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.In this role you willDesign and ship production systems around models, owning integrations, data flows, reliability, and on-call readinessLead discovery and scoping from pre-sales through post-sales, including problem framing, constraints, trade-offs, and a delivery planDefine launch criteria for regulated contexts, outcome metrics, and drive adoption until you prove production impactBuild in sensitive data environments where auditability, validation, and access controls drive architecture decisionsRun evaluation loops that measure model and system quality in life science workflows to drive model and product improvementsDistill production learnings into hardened primitives, reference architectures, and templated workflows that scale across regulated life sciences environments.You might thrive in this role if youBring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; advanced degree or equivalent applied experience preferred in Biomedical Engineering, Computational Biology, Bioinformatics, or a related field.Have owned customer GenAI deployments end-to-end from scoping through production adoption and improved them through evals, error analysis, and iteration.Have delivered AI systems in trial design, regulatory writing, or scientific environments where validation, auditability, and compliance constraints shaped the system.Communicate clearly across scientific, model research, technical, and executive audiences, translating technical concepts for non-technical stakeholders with credibility.Apply systems thinking with high execution standards, consistently turning failures or escalations in regulated environments into new operating standards.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 CartesiaOur mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.About the RoleWe’re hiring a Forward Deployed Engineer to advance our mission of building real-time multimodal intelligence by delivering agentic voice AI solutions directly into production for our customers.Your Impact: Be the driving force behind customer deployments, taking AI solutions from early concept and pilot to production launch with enterprise-grade reliabilityTranslate cutting-edge AI capabilities into practical, high-performance systems tailored to real-world customer needsDesign and implement agentic voice AI solutions that integrate seamlessly into customer workflows and infrastructurePrototype, iterate, and deploy AI-driven systems in close collaboration with enterprise customersWork closely with our customers to define success criteria and ensure they achieve meaningful outcomes on Cartesia’s platformYou’ll have significant autonomy to shape customer solutions and directly impact how cutting-edge AI is deployed at scale across global organizations What You BringTechnical leadership with the ability to execute and deliver zero-to-one solutions in ambiguous, customer-driven environmentsYou have an eye for identifying customer problems and opportunities and can translate them into effective AI-powered solutionsStrong engineering skills enable you to rapidly prototype solutions end to end and evolve them into scalable, production-ready systemsYou’re comfortable diving into new technologies and can quickly adapt your skills to our tech stack (Python on the backend, Go and TypeScript preferred)You communicate complex technical concepts clearly and effectively, and you’re comfortable working directly with customersYou’re good at collaborating cross-functionally and translating customer feedback into actionable product and platform improvementsOur Culture🏢 We’re an in-person team based out of San Francisco. We love being in the office, hanging out together, and learning from each other every day.🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way.🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.

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Our MissionReflection’s mission is to build open superintelligence and make it accessible to all.We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.About the RoleData is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data.As a member of the Data Team, your mission is to ensure that the data used to train our models meets a high bar for quality, reliability, and downstream impact. You will directly shape how our models perform on critical capabilities.Working with world-class researchers on our pre-training teams, you’ll help turn fuzzy notions of “good data” into concrete, measurable standards that scale across large data campaigns. We’re looking for engineers who combine strong engineering fundamentals with a deep curiosity about data quality and its impact on model performance.Working closely with our pre-training teams you will:Own upstream data quality for LLM pre-training; as a specialist or generalist across languages and modalitiesPartner closely with research and pre-training teams to translate requirements into measurable quality signals, and provide actionable feedback to external data vendorsIn addition to human-in-the-loop processes, you will design, validate, and scale automated QA methods to reliably measure data quality across large campaignsBuild reusable QA pipelines that reliably deliver high-quality data to pre-training teams for model trainingMonitor and report on data quality over time, driving continuous iteration on quality standards, processes, and acceptance criteriaAbout YouStrong engineering fundamentals with experience building data pipelines, QA systems, or evaluation workflows for pre-training dataDetail-oriented with an analytical mindset, able to identify failure modes, inconsistencies, and subtle issues that affect data qualitySolid understanding of how data quality impacts pre-training, with the ability to translate quality concerns into concrete signals, decisions, and feedbackExperience designing and validating automated quality checks, including rule-based systems, statistical methods, or model-assisted approaches such as LLM-as-a-JudgeComfortable working autonomously, owning problems end-to-end, and collaborating effectively with researchers, engineers, and operations partnersSkills and QualificationsProficiency in Python and building ML / LLM workflows. Must be comfortable debugging and writing scalable codeExperience working with large datasets and automated evaluation or quality-checking systemsFamiliarity with how LLMs work and can describe how models are trained and evaluatedExcellent communication skills with the ability to clearly articulate complex technical concepts across teamsWhat We Offer:We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models.We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time. Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.

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Our MissionReflection’s mission is to build open superintelligence and make it accessible to all.We’re developing open weight models for individuals, agents, enterprises, and even nation states. Our team of AI researchers and company builders come from DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic and beyond.About the RoleData is playing an increasingly crucial role at the frontier of AI innovation. Many of the most meaningful advances in recent years have come not from new architectures, but from better data.As a member of the Data Team, your mission is to ensure that the data used to train and evaluate our models meets a high bar for quality, reliability, and downstream impact. You will directly shape how our models perform on critical capabilities — agentic tool use, long-horizon reasoning and robust safety alignment.Working with world-class researchers on our post-training teams, you’ll help turn fuzzy notions of “good data” into concrete, measurable standards that scale across large data campaigns. We’re looking for engineers who combine strong engineering fundamentals with a deep curiosity about data quality and its impact on model behaviorWorking closely with our post-training teams you will:Own upstream data quality for LLM post-training and evaluation by analyzing expert-developed datasets and operationalizing quality standards for reasoning, alignment, and agentic use casesPartner closely with research and post-training teams to translate requirements into measurable quality signals, and provide actionable feedback to external data vendorsDesign, validate, and scale automated QA methods, including LLM-as-a-Judge frameworks, to reliably measure data quality across large campaignsBuild reusable QA pipelines that reliably deliver high-quality data to post-training teams for model training and evaluationMonitor and report on data quality over time, driving continuous iteration on quality standards, processes, and acceptance criteriaAbout YouStrong engineering fundamentals with experience building data pipelines, QA systems, or evaluation workflows for post-training data and agentic environmentsDetail-oriented with an analytical mindset, able to identify failure modes, inconsistencies, and subtle issues that affect data qualitySolid understanding of how data quality impacts training (SFT and RL) and evaluation, with the ability to translate quality concerns into concrete signals, decisions, and feedbackExperience designing and validating automated quality checks, including rule-based systems, statistical methods, or model-assisted approaches such as LLM-as-a-JudgeComfortable working autonomously, owning problems end-to-end, and collaborating effectively with researchers, engineers, and operations partnersSkills and QualificationsProficiency in Python and building ML / LLM workflows. Must be comfortable debugging and writing scalable codeExperience working with large datasets and automated evaluation or quality-checking systemsFamiliarity with how LLMs work and can describe how models are trained and evaluatedExcellent communication skills with the ability to clearly articulate complex technical concepts across teamsWhat We Offer:We believe that to build superintelligence that is truly open, you need to start at the foundation. Joining Reflection means building from the ground up as part of a small talent-dense team. You will help define our future as a company, and help define the frontier of open foundational models.We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.Top-tier compensation: Salary and equity structured to recognize and retain the best talent globally.Health & wellness: Comprehensive medical, dental, vision, life, and disability insurance.Life & family: Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time. Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.

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Location 📍: Sydney, Australia (Hybrid - 3 Days In Office)About Us 🚀At Relevance AI, we’re building the home of the AI workforce.Our mission is simple: empower every team to delegate meaningful work to AI agents that think, act, and collaborate like experts.With Relevance AI, anyone can create and manage intelligent agents that handle workflows, decisions, and collaboration - all within one unified platform. Our technology already powers industry leaders such as Canva, Databricks, Confluent, Autodesk, Lightspeed, Rakuten, Aveva, Qualified, and Activision Blizzard, helping them scale excellence across operations, marketing, and sales.We’re backed by Bessemer Venture Partners, Insight Partners, Peak XV, and King River Capital, and raised our Series B in April 2025 to accelerate growth and push the boundaries of agentic automation.Headquartered in San Francisco and Sydney, we operate on a hybrid model and thrive on curiosity, collaboration, and execution - we move fast, think big, and win together.In 2025, we were proud to be named LinkedIn’s #1 Startup in Australia.If you want to define how the world works with AI, join us.The Role 🥳We are seeking exceptional Staff Engineers to join our AI team and build the next generation of AI-powered products. This is a high-impact applied AI role for engineers who want their work to matter. You’ll build and ship real AI features that solve customer problems across multiple industries - turning cutting-edge agentic AI into systems customers rely on in production.This is not your traditional ML or MLOps role. You’ll work across the full stack to design, build, and ship AI-powered workflows, tools, and experiences. Your work will span prompt and context engineering, agent orchestration, backend services, APIs, infrastructure, and user-facing interfaces - often within the same project.You’ll be part of a small high-performing team of AI specialists reporting directly to our co-founder and be deeply embedded across our various Product & Engineering teams. If you’re excited by LLMs, multi-agent systems, and solving hard, real-world AI problems, this role is built for you.Your impact💥Develop Agents and Multi-agent systems: Design and implement AI agent and extend existing agents with new capabilities. This includes managing the agent’s context (using techniques like sub-agents, retrieval based context management, sliding context windows, etc.).Develop Tools for agents: Develop complex tools for agents like computer use, browser use, etc.Multi-agent orchestration and tool calling: Research and develop systems on how agents should collaborate, and how agents should call tools.Fullstack development: Build and maintain production-grade APIs and AI-powered features, from backend services to user-facing experiences.Evaluate and improve: Evaluate AI’s performance using evaluations and tests to then iterate on prompts, agent tools and agents orchestration to improve output quality and reliability.Our Tech Stack (so far) 💻We leverage a modern, scalable, and developer-friendly technology stack to build robust web applications:Frontend: Vue.js, Nuxt, TypescriptBackend: Express.js, Node.js, TypescriptDatabase: MongoDB, PostgreSQLCloud Infrastructure: Vercel, AWS (Lambda, Batch, CloudWatch), TerraformWhat We’re Looking For 🧠Proven staff-level experience in full-stack software development, ideally developing practical and production-ready AI applications or features that utilise Gen AI/ LLMs / RAG.Strong programming skills in Python and Javascript, including experience using AI-assisted coding tools.Deep understanding of foundational models, prompt engineering, and fine-tuning techniques.Understanding of software design, service architecture, and scalable systems.Passion for building AI-enhanced user experiences, not just theoretical ML solutions.Prior start-up or tech company experience is a plus—especially where you’ve worn multiple hats or shaped early products.Bonus: Side projects or open-source contributions involving building AI agents, RAG pipelines, or open-source LLM tooling.Interview Process 💬Talent Interview (virtual)Hiring Manager Interview (virtual)Technical Interviews (onsite)Co-Founder Interview (virtual/ onsite)Why Join Us? 🌟Work at the forefront of AI with a nimble team that is constantly pushing boundaries. We encourage and celebrate ideas that drive our mission forward.We're guided by our five values: truth-seeking, being empathetic, putting the customer first, iterate extremely fast, and building memories.We’ve set high standards in our high-trust, low-ego environment. We hire exceptional people to do the best work of their lives. In return, we reward our people with competitive salaries, equity stake, unparalleled professional growth, and career-defining opportunities.Relevance AI is well-funded by leading investors, including Bessemer Venture Partners, Insights Partners, Peak XV, and King River Capital.As an early team member, you’ll play a key role in shaping our future—including our culture, ways of working, and even the benefits we offer. We’re laying the foundations now, and your ideas can help define what comes next.Benefits (Australia) ✨📈 ESOP – Employee Stock Ownership Plan so you can grow with the company🤖 AI Productivity Benefit – Get up to $1200 USD/year to spend on AI tools, courses, and learning resources that help you work smarter and grow your skills👶 Parental Leave – We offer 12 weeks of paid parental leave for all eligible new parents, and an additional 6 weeks for the birthing parent🎉 Milestone Merch – Celebrate your work anniversaries with customised Relevance AI swag🍿 Food, Drinks & Community – Stay energised with free breakfasts, healthy snacks, and a fully stocked fridge of drinks. Enjoy team lunches provided every Thursday and Friday, plus Uber Eats dinners and regular catered office meals throughout the week. As the home of the AI workforce, we also host vibrant community events featuring thought leaders, industry partners, and the wider tech community.🪩 Quarterly Team Events – Build stronger connections through fun, meaningful team bonding experiences every quarter🏓 Social Clubs – Share your hobbies and interests by joining or starting a club with your teammates. From hiking and chess to board game nights and social committee activities—there’s something for everyone!🧠 Sonder EAP – Access 24/7 mental health and wellbeing support through Sonder, our Employee Assistance Program

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Location 📍: Sydney, Australia (Hybrid - 3 Days In Office)About Us 🚀At Relevance AI, we’re building the home of the AI workforce.Our mission is simple: empower every team to delegate meaningful work to AI agents that think, act, and collaborate like experts.With Relevance AI, anyone can create and manage intelligent agents that handle workflows, decisions, and collaboration - all within one unified platform. Our technology already powers industry leaders such as Canva, Databricks, Confluent, Autodesk, Lightspeed, Rakuten, Aveva, Qualified, and Activision Blizzard, helping them scale excellence across operations, marketing, and sales.We’re backed by Bessemer Venture Partners, Insight Partners, Peak XV, and King River Capital, and raised our Series B in April 2025 to accelerate growth and push the boundaries of agentic automation.Headquartered in San Francisco and Sydney, we operate on a hybrid model and thrive on curiosity, collaboration, and execution - we move fast, think big, and win together.In 2025, we were proud to be named LinkedIn’s #1 Startup in Australia.If you want to define how the world works with AI, join us.The Role 🥳We are seeking Senior Engineers to join our AI team and build the next generation of AI-powered products. This is a high-impact applied AI role for engineers who want their work to matter. You’ll build and ship real AI features that solve customer problems across multiple industries - turning cutting-edge agentic AI into systems customers rely on in production.This is not your traditional ML or MLOps role. You’ll work across the full stack to design, build, and ship AI-powered workflows, tools, and experiences. Your work will span prompt and context engineering, agent orchestration, backend services, APIs, infrastructure, and user-facing interfaces - often within the same project.You’ll be part of a small high-performing team of AI specialists reporting directly to our co-founder and be deeply embedded across our various Product & Engineering teams. If you’re excited by LLMs, multi-agent systems, and solving hard, real-world AI problems, this role is built for you.Your impact💥Develop Agents and Multi-agent systems: Design and implement AI agent and extend existing agents with new capabilities. This includes managing the agent’s context (using techniques like sub-agents, retrieval based context management, sliding context windows, etc.).Develop Tools for agents: Develop complex tools for agents like computer use, browser use, etc.Multi-agent orchestration and tool calling: Research and develop systems on how agents should collaborate, and how agents should call tools.Fullstack development: Build and maintain production-grade APIs and AI-powered features, from backend services to user-facing experiences.Evaluate and improve: Evaluate AI’s performance using evaluations and tests to then iterate on prompts, agent tools and agents orchestration to improve output quality and reliability.Our Tech Stack (so far) 💻We leverage a modern, scalable, and developer-friendly technology stack to build robust web applications:Frontend: Vue.js, Nuxt, TypescriptBackend: Express.js, Node.js, TypescriptDatabase: MongoDB, PostgreSQLCloud Infrastructure: Vercel, AWS (Lambda, Batch, CloudWatch), TerraformWhat We’re Looking For 🧠4+ years in full-stack software development, ideally developing practical and production-ready AI applications or features that utilise Gen AI/ LLMs / RAG.Strong programming skills in Python and Typescript, including experience using AI-assisted coding tools.Deep understanding of foundational models, prompt engineering, and fine-tuning techniques.Understanding of software design, service architecture, and scalable systems.Passion for building AI-enhanced user experiences, not just theoretical ML solutions.Prior start-up or tech company experience is a plus - especially where you’ve worn multiple hats or shaped early products.Bonus: Side projects or open-source contributions involving building AI agents, RAG pipelines, or open-source LLM tooling.Interview Process 💬Talent Interview (virtual)Hiring Manager Interview (virtual)Technical Interviews (onsite)Co-Founder Interview (virtual/ onsite)Why Join Us? 🌟Work at the forefront of AI with a nimble team that is constantly pushing boundaries. We encourage and celebrate ideas that drive our mission forward.We're guided by our five values: truth-seeking, being empathetic, putting the customer first, iterate extremely fast, and building memories.We’ve set high standards in our high-trust, low-ego environment. We hire exceptional people to do the best work of their lives. In return, we reward our people with competitive salaries, equity stake, unparalleled professional growth, and career-defining opportunities.Relevance AI is well-funded by leading investors, including Bessemer Venture Partners, Insights Partners, Peak XV, and King River Capital.As an early team member, you’ll play a key role in shaping our future—including our culture, ways of working, and even the benefits we offer. We’re laying the foundations now, and your ideas can help define what comes next.Benefits (Australia) ✨📈 ESOP – Employee Stock Ownership Plan so you can grow with the company🤖 AI Productivity Benefit – Get up to $1200 USD/year to spend on AI tools, courses, and learning resources that help you work smarter and grow your skills👶 Parental Leave – We offer 12 weeks of paid parental leave for all eligible new parents, and an additional 6 weeks for the birthing parent🎉 Milestone Merch – Celebrate your work anniversaries with customised Relevance AI swag🍿 Food, Drinks & Community – Stay energised with free breakfasts, healthy snacks, and a fully stocked fridge of drinks. Enjoy team lunches provided every Thursday and Friday, plus Uber Eats dinners and regular catered office meals throughout the week. As the home of the AI workforce, we also host vibrant community events featuring thought leaders, industry partners, and the wider tech community.🪩 Quarterly Team Events – Build stronger connections through fun, meaningful team bonding experiences every quarter🏓 Social Clubs – Share your hobbies and interests by joining or starting a club with your teammates. From hiking and chess to board game nights and social committee activities—there’s something for everyone!🧠 Sonder EAP – Access 24/7 mental health and wellbeing support through Sonder, our Employee Assistance Program

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Mirage is the leading AI short-form video company. We’re building full-stack foundation models and products that redefine video creation, production and editing. Over 20 million creators and businesses use Mirage’s products to reach their full creative and commercial potential.We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you’ll have an opportunity to have an outsized impact on our products and our company's culture.Our ProductsCaptions Mirage Studio Our TechnologyAI Research @ MirageMirage Model AnnouncementSeeing Voices (white-paper)Press CoverageTechCrunchLenny’s PodcastForbes AI 50Fast CompanyOur InvestorsWe’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) We do not work with third-party recruiting agencies, please do not contact us** About the role This role focuses on designing and building intelligent systems that power creative workflows for short-form video. You’ll help shape how AI-driven experiences reduce friction, accelerate learning, and unlock new creative possibilities for our users—while experimenting with emerging models and techniques to bring these experiences to life in production. Applied AI engineers work across product, machine-learning, and systems engineering—owning meaningful problems end-to-end and helping define how our models are used across the product.ResponsibilitiesBuild and ship end-to-end AI-powered products and systems that meaningfully improve creative workflows, balancing quality, performance, and reliabilityIntegrate state-of-the-art models, combining internal research and external capabilities to unlock new product experiencesMeasure and improve system quality in production, using experimentation, evaluation frameworks, and real-world feedback to guide iterationDesign the systems that support intelligent behavior, including how models gather context, make decisions, and operate efficiently at scaleWhat Makes You a Great Fit5+ years of professional industry experienceA track record of designing and developing ML systems in productionDeep experience with context engineering: RAG systems, token optimization, context management at scaleExperience building evaluation systems and agentic infrastructure (context gathering, tool selection)Exceptional problem solving fundamentals and ability to learn quickly in a rapidly evolving spaceAble to operate effectively in an extremely fast-paced environment and scope and deliver projects end-to-endEven better if...You have worked with multi-agent architecturesYou have experience fine-tuning LLMs for specific use casesYou have a pulse on where generative media and agentic AI technology is goingYou are grounded, collaborative, and willing to do whatever it takes to help the team winYou have been a startup founder or an early engineer at oneBenefits:Comprehensive medical, dental, and vision plans401K with employer matchCommuter BenefitsCatered lunch multiple days per weekDinner stipend every night if you're working late and want a bite! Grubhub subscriptionHealth & Wellness Perks (Talkspace, Kindbody, One Medical subscription, HealthAdvocate, Teladoc)Multiple team offsites per year with team events every monthGenerous PTO policyCaptions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.Please note benefits apply to full time employees only.

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About SolidroadBuilding something great is addictive. It’s like discovering your favorite TV show mid-season, except you're helping write the next episode. It’s like unboxing a new gadget, except you’re the one designing it. You shape how it feels, how it works, and how people react when they use it.At Solidroad we're solving a big, messy, exciting problem: how do you scale customer support without losing what makes humans amazing? Warmth, empathy, intuition. We’re using AI, generative tech, and real-time simulations to make this happen. It's ambitious, difficult, and genuinely new.About the roleWe're looking for a senior engineer who sees this role as more than just a job. It should feel like signing up for a job and a hobby. Or a job and a triathlon. Or a job and an advanced language course. You’ll shape our technical decisions, own major parts of our product, mentor your teammates, and push yourself in ways you might not expect. It’ll stretch your skills and fill your life in a deeply rewarding way. You’ll write impactful code (full-stack, frontend, backend, AI integrations; it's all on the table), and make critical decisions about architecture, tooling, and product direction. There will be challenging moments, but also regular moments of genuine "wow, we built that" pride.What you'll actually do day-to-dayLead Development of Advanced Prompt Engineering and Retrieval Pipelines Architect and build scalable solutions handling thousands of customer conversations daily across integrations like Zendesk, Intercom, and Salesforce. You’ll leverage cutting-edge generation pipelines to deliver rapid insights, accurate analysis, and meaningful customer interaction scoring.Architect Real-Time Multimodal Simulations Own the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi. Your simulations will dynamically adapt to user input, creating genuinely immersive learning environments.Drive High-Performance User Experiences Set the technical standard for intuitive, lightning-fast interfaces built with Next.js. You'll ensure our UIs handle complex AI interactions seamlessly, even under demanding workloads, and mentor others to achieve the same standard.Our Team & CultureWe’re a focused group working full-time in our San Francisco and Dublin offices. We’re there five days a week because building something ambitious means collaborating closely, solving problems together, sharing ideas spontaneously, and occasionally challenging each other to padel matches, cold plunges, or karaoke evenings. We're intentional about creating a culture that's mature, supportive, and fun. You'll be joining experienced founders who've done this before, alongside a tight-knit team genuinely excited about building something impactful.We hope youHave at least 4 years of engineering experience, ideally at a startup (Series A to C), where you've helped ship complex, customer-facing products.Bring strong technical leadership, including experience mentoring other engineers, leading technical decisions, or architecting significant product areas.Have deep expertise in modern web technologies, product architecture, or AI integrations—bonus points if you’ve worked on notable or challenging projects we can explore together.The good, the bad, and the honest truthThe highs here are incredibly high, direct collaboration with founders who’ve done this before, significant ownership, and a product you'll feel deeply proud of. The lows are that you'll need to move fast, navigate ambiguity, and sometimes tackle tough problems solo. But the reality is that startups are a bit like a sport or an instrument: you invest in it not just because you have to, but because you genuinely want to be better tomorrow than you are today.If that sounds exciting, don’t second-guess yourself. Get in touch. Send us something you've built that you're proud of (GitHub, personal site, anything goes) and a short note about who you are and why this feels right to you. We value enthusiasm, ambition, and curiosity just as much as your technical experience.

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About SolidroadBuilding something great is addictive. It’s like discovering your favorite TV show mid-season, except you're helping write the next episode. It’s like unboxing a new gadget, except you’re the one designing it. You shape how it feels, how it works, and how people react when they use it.At Solidroad we're solving a big, messy, exciting problem: how do you scale customer support without losing what makes humans amazing? Warmth, empathy, intuition. We’re using AI, generative tech, and real-time simulations to make this happen. It's ambitious, difficult, and genuinely new.About the roleWe're looking for a senior engineer who sees this role as more than just a job. It should feel like signing up for a job and a hobby. Or a job and a triathlon. Or a job and an advanced language course. You’ll shape our technical decisions, own major parts of our product, mentor your teammates, and push yourself in ways you might not expect. It’ll stretch your skills and fill your life in a deeply rewarding way. You’ll write impactful code (full-stack, frontend, backend, AI integrations; it's all on the table), and make critical decisions about architecture, tooling, and product direction. There will be challenging moments, but also regular moments of genuine "wow, we built that" pride.What you'll actually do day-to-dayLead Development of Advanced Prompt Engineering and Retrieval Pipelines Architect and build scalable solutions handling thousands of customer conversations daily across integrations like Zendesk, Intercom, and Salesforce. You’ll leverage cutting-edge generation pipelines to deliver rapid insights, accurate analysis, and meaningful customer interaction scoring.Architect Real-Time Multimodal Simulations Own the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi. Your simulations will dynamically adapt to user input, creating genuinely immersive learning environments.Drive High-Performance User Experiences Set the technical standard for intuitive, lightning-fast interfaces built with Next.js. You'll ensure our UIs handle complex AI interactions seamlessly, even under demanding workloads, and mentor others to achieve the same standard.Our Team & CultureWe’re a focused group working full-time in our San Francisco and Dublin offices. We’re there five days a week because building something ambitious means collaborating closely, solving problems together, sharing ideas spontaneously, and occasionally challenging each other to padel matches, cold plunges, or karaoke evenings. We're intentional about creating a culture that's mature, supportive, and fun. You'll be joining experienced founders who've done this before, alongside a tight-knit team genuinely excited about building something impactful.We hope youHave at least 4 years of engineering experience, ideally at a startup (Series A to C), where you've helped ship complex, customer-facing products.Bring strong technical leadership, including experience mentoring other engineers, leading technical decisions, or architecting significant product areas.Have deep expertise in modern web technologies, product architecture, or AI integrations—bonus points if you’ve worked on notable or challenging projects we can explore together.The good, the bad, and the honest truthThe highs here are incredibly high, direct collaboration with founders who’ve done this before, significant ownership, and a product you'll feel deeply proud of. The lows are that you'll need to move fast, navigate ambiguity, and sometimes tackle tough problems solo. But the reality is that startups are a bit like a sport or an instrument: you invest in it not just because you have to, but because you genuinely want to be better tomorrow than you are today.If that sounds exciting, don’t second-guess yourself. Get in touch. Send us something you've built that you're proud of (GitHub, personal site, anything goes) and a short note about who you are and why this feels right to you. We value enthusiasm, ambition, and curiosity just as much as your technical experience.

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About the Internship As a Research Intern at Snorkel AI, you’ll contribute to internal research and academic collaborations—helping explore and validate new ideas that may shape future publications, open-source artifacts, and long-term product directions. This is a research-first role, designed for interns who want to do deep technical work with real-world relevance. You’ll work closely with Snorkel researchers on open-ended projects and produce clear research outputs (experiments, prototypes, internal writeups, and potentially publications depending on project fit and timing). What You’ll Do Develop and evaluate new methods for data development for foundation models and enterprise AI systems (e.g., dataset construction, augmentation, synthetic data, and evaluation). Research supervision and evaluation techniques such as rubrics and verifiable rewards. Design experiments and run rigorous empirical studies (ablations, benchmarks, error analysis). Build lightweight research prototypes and tooling in Python to support internal studies. Collaborate with academic partners and internal research teams—reading papers, proposing hypotheses, and iterating quickly. Example Project Areas Projects vary by mentor and collaboration needs, but may include: Synthetic data generation + filtering for specialized tasks Evaluation datasets and benchmarks for LLM / RAG / agent behavior Data-centric methods for improving reliability, calibration, and failure-mode coverage Evaluating HITL data annotation processes, gaps, and improvements What We’re Looking For Current student in a PhD in ML/AI/CS. Strong ML fundamentals and demonstrated research ability (papers, preprints, or substantial research artifacts). Excellent Python skills and experience with modern ML tooling (PyTorch, NumPy, etc.). Ability to operate in ambiguous, research-driven problem spaces with strong experimentation habits. Clear communication: can write concise technical notes and present findings. Nice to have Prior work on evaluation, data curation, synthetic data, weak supervision, NLP, or multimodal ML. Experience collaborating with academic labs or participating in research programs. Internship Details Duration: Summer (flexible start/end) Location: Hybrid (Redwood City/SF) or Remote (US) Compensation: Competitive, commensurate with experience Why Snorkel Research Work with a research org advancing data-centric AI and foundation-model development, in close partnership with labs and enterprises.  Join a company with deep research roots and a substantial body of peer-reviewed work in this space.  Get mentorship and ownership on projects that can influence long-term research direction. Be Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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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:$190,000—$230,000 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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Who we are:TrustLab deploys cutting edge solutions to evaluate AI agents, models and apps for enterprise customers. With a 5 year track record working with large and small clients including social media companies and digital market places, and guided by founders who previously worked in senior leadership positions at Google, YouTube, TikTok, and Reddit, we are creating industry leading LLM based solutions for agentic system evaluation and labeling. Our approach includes human-in-the-loop and LLM-as-a-judge technologies, with a focus on rapid innovation and production level scaling. You’ll join a small, mission-driven team where your contributions have a direct impact on real-world issues.What you’ll do: At TrustLab, your work won’t live in theory - it will power live systems used at large scale. You’ll develop, tune, and optimize LLM-driven solutions that interpret and reason about complex digital content, while experimenting rapidly from design to deployment and seeing immediate feedback from real-world use cases. Partnering closely with other engineers, researchers, and product leaders, you’ll pioneer new approaches to model training and evaluation, taking ownership from early R&D through to production launches, and ensuring your work directly shapes how millions of people experience AI-powered content.Key Responsibilities:Train, evaluate, and monitor new and improved LLMs and other algorithmic modelsTest and deploy content moderation models in production, and iterate based on real-world performance metrics and feedback loops.Develop medium to long-term vision for content understanding-related R&D, working with management, product, policy & operations, and engineering teams.Take ownership of results delivered to customers, pushing for change in approach where needed and taking the lead on cross-functional execution.What we’re looking for:Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Ph.D. is a plus. Proficiency in Python. Experience with AWS and CI/CD processes & tools is a strong plus.Experience with prompt-engineering techniques and familiarity with multiple LLM providers.Several years of industry experience in NLP / Computer Vision, or making LLM’s work in production for non-trivial use cases, incl. familiarity with evaluation metrics for classification tasks and best practices for handling imbalanced datasets.Hands-on experience with debugging issues in production environments, especially on AWS.Strong track record delivering results under time and resource pressureWhy Join Us?Work with a group of renown industry leaders in AI and Online Safety to shape the future of the industry.Ample opportunity and support for growth, as a technical individual contributor, or manager.Apply AI technology to real-world business use cases at a significant scale, with blue chip customersWork as part of a team where you can know everyone, but don’t have to do everyone’s job.Competitive compensation, comprehensive benefits, and hybrid in-office policy.

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About the Team The Knowledge Innovation team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the RoleWe’re looking for Full Stack Engineers who're passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. In this role, you will:Own the end-to-end development lifecycle for new platform capabilities and integrations with other systemsCollaborate closely with engineers, data scientists, information systems architects, and internal customers to understand their problems and implement effective solutionsWork with product and research team to share relevant feedback and iterate on applying their latest modelsAbout 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 SunoSuno is a music company built to amplify imagination. Powered by the world’s most advanced AI music model, Suno offers an unparalleled creative platform that includes Suno Studio, a breakthrough generative audio workstation. From shower-singers to aspiring songwriters to seasoned artists, Suno empowers a global community to create, share, and discover music—unlocking the joy of musical expression for all. About the RoleWe're looking for someone to lead recommendations at Suno. You'll be instrumental in building Suno's music discovery and recommendation systems. You'll help define how millions of users discover, create, and engage with music on our platform by shaping both the systems and the team that makes it happen.This role is for someone who has deep experience with recommendation systems at scale and is energized about building a new and better one. You're excited to apply and adapt your expertise in a new context and grow an excellent team to get there.Check out the Suno version of this role here! What You'll DoShape Suno's recommendation vision, strategy, and technical directionPartner with leaders across product, engineering, and research to decide how recommendations evolve with our platformLead the building of a full recommendations system from the ground up, from prototyping and evaluating approaches to experimentation to deploying at scaleBuild and grow a recommendations team What You'll Need5+ years building recommendation systems at scale, with at least 2+ years leading teams and owning the development of recommendation systems in productionDeep technical expertise of what's cutting edge and the ability to get there through practical, iterative stepsStrong collaboration skills and the ability to work with leaders across the company to influence directionPassion for what Suno is building and excitement about defining the future of music discoveryAdditional Notes: Applicants must be eligible to work in the US.This is an onsite role in our SF office Perks & Benefits for Full-Time EmployeesGenerous Company Equity Package401(k) with 3% Employer Match & Roth 401(k)Unlimited PTO & Sick TimeMedical, Dental, & Vision Insurance (PPO w/ HSA & FSA options)Continued / Creative Education StipendGenerous Commuter AllowanceIn-Office Lunch (5 days per week)Suno is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the Massachusetts Fair Chance in Employment Act, NYC Fair Chance Act, LA City Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.

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About CartesiaOur mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.About The RoleTo build truly global AI, our models must be trained on data that reflects the world's diversity of languages and cultures. We are searching for a Machine Learning Engineer to own the quality and coverage of the data behind our models. You will be our in-house expert on global data, ensuring our models perform exceptionally well across dozens of languages. You have a keen eye for linguistic nuance, and a passion for building inclusive and representative datasets at scale.Your ImpactDesign and build large-scale datasets for model training.Build evaluations of speech models, both via manual annotation and at scale with automated metrics.Implement techniques for steering data generation to improve model intelligence through data and mitigate bias.Build automated quality control systems to validate and filter generated dataPartner with product teams to ensure support for key languages and markets.What You BringExperience building or working with large multilingual datasetsExperience with generative models (speech, text, or multimodal).Ability to help guide human annotation and evaluation across multiple languages.Strong applied ML background with a focus on data-centric approaches.Excitement for building scalable systems that bridge research and production.What We Offer🍽 Lunch, dinner and snacks at the office.🏥 Fully covered medical, dental, and vision insurance for employees.🏦 401(k).✈️ Relocation and immigration support.🦖 Your own personal Yoshi.Our Culture🏢 We’re an in-person team based out of San Francisco. We love being in the office, hanging out together, and learning from each other every day.🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way.🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.

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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!Why this role?We’re a fast-growing startup building production-grade AI agents for enterprise customers at scale. We’re looking for Applied AI Engineers who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs)—from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows.In this role, you’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one.You’ll collaborate closely with customers, product, and platform teams, and help shape how agentic systems are built, evaluated, and deployed at scale.What You’ll DoWork with enterprise customers and internal teams to turn business workflows into scalable, production-ready agentic AI systems.Design and build LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability.Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions.Define and apply evaluation and quality standards to measure success, failures, and regressions.Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails.Contribute to shared frameworks and patterns that enable consistent delivery across customers.Required Skills & ExperienceBachelor’s degree in Computer Science or a related technical field.Strong programming skills in Python and/or JavaScript/TypeScript.3+ years of experience building and shipping production software; 2+ years working with LLMs or AI APIs.Hands-on experience with modern LLMs (e.g., GPT, Claude, Gemini), vector databases, and agent/orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, or custom solutions).Practical experience with RAG, agent workflows, evaluation, and performance optimization.Strong agent design skills, including prompt engineering, tool use, multi-step agent workflows (e.g. ReAct), and failure handling.Ability to reason about and balance trade-offs between customization and reuse, as well as autonomy, control, cost, latency, and risk.Strong communication skills and experience leading technical discussions with customers or partners.Nice-to-HaveExperience working in a fast-moving startup environment.Prior work delivering AI or automation solutions to enterprise customers.Familiarity with human-in-the-loop workflows, fine-tuning, or LLM evaluation techniques.Experience with cloud deployment and production operations for AI systems.Background in applied ML, NLP, or decision systems.Additional RequirementsStrong written and verbal communication skills.Ability and interest to travel up to 25%, flexible.Why Join UsBuild production-grade AI agents used in real enterprise workflows.Operate at scale while retaining end-to-end ownership.Work on hard problems in agent design, evaluation, and reliability.Shape shared platforms and standards, not just individual features.Move fast with a high bar for quality, safety, and reliability.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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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!Why This Role Is DifferentThis is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will:Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems.Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques.Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models.Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab.Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineering, and core-model influence as directly as this one.What You’ll DoTechnical Leadership & Solution DesignContribute to the design and delivery of custom LLM solutions for enterprise customers.Translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies.Modeling, Customization & Foundations ContributionBuild custom models using Cohere’s foundation model stack, CPT recipes, post-training pipelines (including RLVR), and data assets.Develop SOTA modeling techniques that directly enhance model performance for customer use-cases.Contribute improvements back to the foundation-model stack — including new capabilities, tuning strategies, and evaluation frameworks.Customer-Facing Technical ImpactWork as part of Cohere’s customer facing MLE team to identify high-value opportunities where LLMs can unlock transformative impact to our enterprise customers.You May Be a Good Fit If You Have:Technical FoundationsStrong ML fundamentals and the ability to frame complex, ambiguous problems as ML solutions.Fluency with Python and core ML/LLM frameworks.Experience working with (or the ability to learn) large-scale datasets and distributed training or inference pipelines.Understanding of LLM architectures, tuning techniques (CPT, post-training), and evaluation methodologies.Demonstrated ability to meaningfully shape LLM performance.Experience & LeadershipA broad view of the ML research landscape and a desire to push the state of the art.MindsetBias toward action, high ownership, and comfort with ambiguity.Humility and strong collaboration instincts.A deep conviction that AI should meaningfully empower people and organizations.Join UsThis is a pivotal moment in Cohere’s history. As an MTS in Applied ML, you will define not only what we build — but how the world experiences AI. If you're excited about building custom models, solving generational problems for global organizations, and shaping frontier-model capabilities, we’d love to meet 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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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!Why This Role Is DifferentThis is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will:Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems.Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques.Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models.Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab.Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineering, and core-model influence as directly as this one.What You’ll DoTechnical Leadership & Solution DesignLead the design and delivery of custom LLM solutions for enterprise customers.Translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies.Modeling, Customization & Foundations ContributionBuild custom models using Cohere’s foundation model stack, CPT recipes, post-training pipelines (including RLVR), and data assets.Develop SOTA modeling techniques that directly enhance model performance for customer use-cases.Contribute improvements back to the foundation-model stack — including new capabilities, tuning strategies, and evaluation frameworks.Customer-Facing Technical ImpactWork closely with enterprise customers to identify high-value opportunities where LLMs can unlock transformative impact.Provide technical leadership across discovery, scoping, modeling, deployment, agent workflows, and post-deployment iteration.Establish evaluation frameworks and success metrics for custom modeling engagements.Team Mentorship & Organizational ImpactMentor engineers across distributed teams.Drive clarity in ambiguous situations, build alignment, and raise engineering and modeling quality across the organization.You May Be a Good Fit If You Have:Technical FoundationsStrong ML fundamentals and the ability to frame complex, ambiguous problems as ML solutions.Fluency with Python and core ML/LLM frameworks.Experience working with large-scale datasets and distributed training or inference pipelines.Understanding of LLM architectures, tuning techniques (CPT, post-training), and evaluation methodologies.Demonstrated ability to meaningfully shape LLM performance.Experience & LeadershipExperience engaging directly with customers or stakeholders to design and deliver ML-powered solutions.A track record of technical leadership at a team level.A broad view of the ML research landscape and a desire to push the state of the art.MindsetBias toward action, high ownership, and comfort with ambiguity.Humility and strong collaboration instincts.A deep conviction that AI should meaningfully empower people and organizations.Join UsThis is a pivotal moment in Cohere’s history. As an MTS in Applied ML, you will define not only what we build — but how the world experiences AI. If you're excited about building custom models, solving generational problems for global organizations, and shaping frontier-model capabilities, we’d love to meet 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 usAt Sierra, we’re creating a platform to help businesses build better, more human customer experiences with AI. We are primarily an in-person company based in San Francisco, with growing offices in Atlanta, New York, London, France, Singapore, and Japan.We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and Family. These values are the foundation of our work, and we are committed to upholding them in everything we do.Our co-founders are Bret Taylor and Clay Bavor. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. What you’ll doSierra’s engineering team has ~40 mostly senior engineers, including Mihai, Belinda, Arya, and Wei. We work in small, autonomous teams oriented around customer problems. Here are some examples of what you’ll work on:Simulation & Benchmarking: How can we craft a simulation platform to test AI agents against every real-world scenario imaginable? (See 𝜏-Bench)Content Management: How do we create intuitive, no-code tools that allow anyone to guide and test AI agents?Agent Development Lifecycle: How do we adapt traditional software development methodologies to accommodate AI agents’ non-deterministic behavior, natural language interactions, and reliance on large language models? (See Sierra’s ADLC)Generative Agent Development: How do we accelerate agent creation using generative tools like Cursor and Claude Code? Can we build self-improving systems based on real-world interactions, customer-driven feedback, and self-play?What you'll bringA passion for being on the frontier of AI products.Motivation and high-agency to drive outcomes - we have a high-autonomy culture and each team member has lots of agency to overcome obstacles and achieve customer impact.Alignment to our company values throughout your work, notably finding a balance between Craftsmanship, Customer Obsession, and Competitive Intensity.4+ years hands-on experience building production products and systems.Experience and comfort to build and ship full-stack solutions.Degree in Computer Science or related field, or equivalent professional experience.Even better...Experience building AI-powered products.A sharp eye for design.Experience with Go and Typescript.Experience building developer tooling, programming languages, or databases.Leadership experience on technical projects or teams.Our valuesTrust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.What we offerWe want our benefits to reflect our values and offer the following to full-time employees:Flexible (Unlimited) Paid Time OffMedical, Dental, and Vision benefits for you and your familyLife Insurance and Disability BenefitsRetirement Plan (e.g., 401K, pension) with Sierra matchParental LeaveFertility and family building benefits through CarrotLunch, as well as delicious snacks and coffee to keep you energized Discretionary Benefit Stipend giving people the ability to spend where it matters mostFree alphorn lessonsThese benefits are further detailed in Sierra's policies and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies.Be you, with usWe're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.