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Production Supervisor Jobs

8,337 active opportunities · Updated for October 2026

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Explore current production supervisor jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Stripe
📍 South San Francisco• Full-time• $212K – $318K/yr
2mo ago

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. Design systems to speed up the time from idea to deployment of new models. Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. Develop pipelines and automated processes to train and evaluate models in offline and online environments. Integrate ML models into production systems and ensure their scalability and reliability. Collaborate with product and strategy partners to propose, prioritize, and implement new product features. Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production. Must have two (2) years of experience in each of the following: ML algorithms and model architectures; Designing, training and evaluating machine learning models; Productionizing and deploying machine learning models at scale; Orchestrating data pipelines and leveraging large-s

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Anthropic
📍 Ca New York City• $405K – $485K/yr
2mo ago

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Network Security team's remit is to secure Anthropic's networks across our cloud providers and our bare-metal AI data centers. We own egress and ingress controls, network segmentation, private connectivity between environments, and encryption in transit. We design, build, and maintain these controls, and we write the software that deploys, enforces, and monitors them. These controls protect our model weights, customer data, and internal assets. We are hiring an Engineering Manager to lead this team. Anthropic is adding data center sites and cloud regions quickly, and the team will grow with that work. In this role you will set the team's charter, practices, and priorities. You will partner with our infrastructure networking, cluster, and data center teams so security is built into network designs from the start. The goal is secure-by-default networking that lets research and product teams use compute in any environment without slowing them down. Key responsibilities We're hiring an Engineering Manager to lead a Network Security Engineering team in executing across critical initiatives including, but not limited to: Own the network security roadmap: threat model from the management plane through Kubernetes and cloud interconnects, decide what to build, and deliver it Be able to reason about the design and implementation of default-deny ingress and egress, segmentation between research, training, and production, private connectivity, and mTLS/service identity across every environment Ship these as secure-by-default primitives so new clusters, VPCs, and data center links inherit the right boundaries without security on

kubernetesailogistics
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2mo ago

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As an AI Accelerator Systems Software Technical Program manager at OpenAI, you will help bring our chips/system hardware roadmap to life, navigating an array of technical and partnership challenges. We’re looking for people excited to push the frontiers of computing by navigating technical explorations and are passionate about building. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Manage the end-to-end software development from design to implementation for our AI acceleration systems, working across technical, cross-functional and external stakeholders Lead planning and scheduling of AI system software designs with our strategic partners and vendors Coordinate and lead internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: Have experience as a software technical program manager for data center system products (server, GPU, TPU, networking, storage and so on) taking products from concept to volume in a data center environment ensuring the systems scale with high quality Know end-to-end software development program management techniques from concept, design, production, deployment into the data center Want to help design some of the world’s largest supercomputing systems, working at the edge of complex hardware challenges Enjoy working with and enabling world-clas

awsrestai
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Spotify
📍 London• Full-time• Remote
2mo ago

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. We are the Voice Production Team, the creative team behind Spotify’s AI voice experiences. We think about AI voices from a casting perspective — including voice type, age and gender — and from a performance perspective, recognizing that a voice may need to perform differently for DJ than it does for an audiobook recap. We bring expertise in voice casting, direction, recording and production, and work closely with Speak to set the quality bar for AI voice models across experiences including AI DJ, Generative AI Ads, Personalized Podcasts, Agent Voice Chat and more. As a Senior Product Quality Analyst, you’ll bring a dedicated evaluation perspective to the team. You’ll own how we define and measure AI voice quality, bringing together Voice Production’s creative bar, Speak’s technical bar and the wider industry bar. Your goal won’t simply be to determine whether Spotify has the “best” AI voice technology on the market. You’ll help us answer a more important question: is our technology the best at serving Spotify’s specific needs? What You'll Do Own the quality bar for Spotify’s AI voice models, defining what “good enough” means for different products, audiences, languages and use cases. Independently design evaluation rubrics and build an evaluation approach that measures qualities such as naturalness, tone, pacing, pronunciation, accent, audio quality and overall experience. Plan and carry out evaluation campaigns, turning qualitative and quantitative findings into clear recommendations for Voice Production, Speak and product team

REMOTEmachine learningairecruitment
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Figma
📍 Ca New York• Full-time• $153K – $376K/yr
2mo ago

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Application Platform is part of Product Platform within Figma’s Infrastructure organization. We build shared foundations that help engineers ship backend product work quickly, safely, and reliably. The team owns a large Ruby application that powers Figma’s REST APIs, asynchronous jobs, and workflow orchestration. Our systems sit on critical production paths and shape the day-to-day experience of backend engineers across Figma. We’re looking for an experienced backend engineer with meaningful production Ruby experience who enjoys building for other engineers. You don’t need to be a Ruby language specialist. You should be comfortable making informed tradeoffs in a substantial shared codebase and turning recurring problems into durable systems, tools, and paved paths that improve engineering velocity across the company. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Design and evolve shared Ruby frameworks for REST APIs, asynchronous jobs, workflow orchestration, and data access Improve the availability, reliability, scalability, and performance of backend systems that support critical product functionality Modernize a large Ruby codebase through safe architectural changes, including moving REST APIs from Sinatra toward Rails and introducing stronger endpoint abstractions and type safety Make backend development faster by improving hot reloading, local workflows, test infrastructure, CI reliability, debugging tools,

awskubernetesai
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Modal
📍 New York• Full-time• $150K – $270K/yr
2mo ago

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for a Detection & Response Engineer to build the systems that help us identify, investigate, and respond to threats across our platform. This is an engineering role focused on automation. You'll build detections, investigation tooling, and response capabilities that scale with our infrastructure, using AI where it meaningfully improves signal, investigation speed, and operational effectiveness. You'll work closely with infrastructure, platform, and security engineers to ensure every incident makes the platform more resilient. What You'll Work On: Detection Engineering Design and build high-fidelity detections for attacks, abuse, and anomalous behavior across our infrastructure and production systems Continuously improve detections based on telemetry, threat intelligence, and lessons learned from incidents Improve visibility across cloud infrastructure, containers, identity system

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OpenAI
📍 San Francisco• Full-time
2mo ago

About the Team The Demo Studio is responsible for translating OpenAI’s most advanced capabilities into tangible, high-impact experiences for customers. We design and deliver the demos, applications, and environments that define how executives understand what is possible with AI. Our work sits at the intersection of product, engineering, design, and go-to-market. We operate as a hybrid of product studio and live production team, building experiences that are both technically credible and narratively compelling. About the Role We’re looking for a Demo Studio Lead to own the end-to-end demo experience for OpenAI’s major events, webinars, and strategic programs. This is a highly cross-functional role focused on translating cutting-edge AI capabilities into clear, compelling, and production-ready experiences. You will own the full demo portfolio for an event or initiative, spanning mainstage moments, breakout experiences, booths, and supporting content. You’ll define the narrative, architect workflows, build high-fidelity demo environments, direct presenters, and ensure flawless execution in live environments. This is not a traditional sales engineering, presentation, or narrowly scoped design role — it requires a combination of product thinking, technical fluency, storytelling, systems design, and operational excellence. A key part of the role is presenting the work directly: delivering live demonstrations to executive, technical, and industry audiences across mainstage, breakout, customer, and recorded settings. This role is ideal for someone who thrives in ambiguity, operates with strong ownership, and is excited about shaping how the world experiences AI firsthand. This is a hybrid role that can be based in either San Francisco or New York. In this role, you will: Own the end-to-end demo experience across OpenAI-hosted summits, webinars, third-party industry events, and strategic executive demonstrations. Translate approved product positioning, real OpenAI capabiliti

awsrestai
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Baseten
📍 San Francisco• Full-time
2mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As the Head of IT at Baseten, you will build, scale, and secure our internal technology function to support our rapid growth. Reporting to our Chief Information Security Officer, you will lead and mentor a team of 5+ IT engineers, leading the charge to transition Baseten from startup-era IT to a highly automated, enterprise-ready IT organization. You will take full ownership of corporate IT infrastructure, Helpdesk operations, corporate identity management, device lifecycles, and vendor procurement. As we scale to support the world’s most dynamic AI companies, you will ensure our internal systems scale seamlessly with our headcount, providing a secure, frictionless, and world-class technology experience for all Baseten employees. RESPONSIBILITIES Team Leadership: Manage, mentor, and grow a team of IT engineers, fostering a high-performance culture focused on technical excellence and end-user satisfaction. Helpdesk Operational Excellence: Build a fast-response support function by establishing clear response SLAs, tracking employee satisfaction metrics, and formalizing on-call and incident response processes. Zero-Touch Automation: Architect and implement automated employee onboarding, offboarding, and role-based access changes through deep integrations across HRIS, MDM, and IAM systems. SaaS Management & Procurement: Establish comprehensive SaaS management processes to eliminate shadow IT, automate access w

machine learningaigo
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O
2mo ago

About the Team The AI Deployment Management (ADM) team enables organizations to turn OpenAI products into real, sustained impact through world-class enablement and training execution. Our mission is to help customers successfully adopt and operationalize AI across their organizations. We partner with enterprises to translate the potential of OpenAI’s technology into durable capability—through structured training, technical enablement, and scalable deployment programs. By helping customers move from experimentation to production, the ADM team accelerates time-to-value, deepens product adoption, and helps make OpenAI indispensable to how organizations work. About the Role The AI Deployment Manager role is a specialist post-sales enablement role focused on delivering high-impact enablement and adoption services across OpenAI’s product suite. This role is responsible for designing and delivering technical enablement experiences that support a repeatable adoption framework– driving sustained activation, expanding breadth and depth of usage, and measurable business value across OpenAI’s product suite, including ChatGPT Enterprise, Codex, Agents, and the API. This includes helping customers understand and correctly apply the deployment harnesses, evaluation layers, and operational controls required for reliable use. This role blends deep technical fluency, instructional design, and customer advisory. You will lead live trainings, workshops, and adoption interventions for audiences ranging from hands-on builders to executive leaders, helping customers understand not just what OpenAI’s products can do, but how to use them effectively in real-world contexts. Success in this role means accelerating customer confidence, increasing product adoption, supporting successful launches of new product capabilities, and helping customers translate technical features into tangible outcomes. This role is based in our Tokyo Office. We use a hybrid work model of 3 days in the office per wee

awsrestai
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OpenAI
📍 San Francisco• Full-time
2mo ago

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

awsrestai
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About the Team ChatGPT relies on a large and growing GPU fleet to serve inference workloads reliably and efficiently. Our team builds the software, tooling, and operational systems that help manage this fleet at scale. We work across production engineering, distributed systems, capacity management, and operational automation to improve reliability, reduce manual work, and make better use of available compute. About the Role We are looking for a software engineer with experience building or operating large-scale production systems. You will develop the systems that help manage the GPU fleet powering ChatGPT, including tooling for fleet health, capacity planning, operational automation, and incident response. You will work closely with infrastructure, research, and product engineering teams to improve reliability, developer productivity, and compute utilization. This role is a good fit for engineers who enjoy solving complex operational problems and building software that makes production infrastructure easier to run at scale. In This Role, You Will Build software and internal tools to manage large-scale GPU infrastructure supporting ChatGPT inference. Develop systems for capacity planning, fleet health monitoring, and resource utilization. Automate operational workflows, including incident detection, diagnosis, and response. Identify and address bottlenecks affecting fleet reliability, scalability, and performance. Partner with infrastructure, research, and product engineering teams to improve the compute platform. You Might Thrive in This Role If You Have experience operating large-scale production infrastructure, GPU clusters, or other compute-intensive distributed systems. Have a background in production engineering, site reliability engineering, infrastructure engineering, or platform engineering. Have built software that automates operational workflows and reduces manual work. Have worked with distributed infrastructure, cluster orchestration, or large-scale int

pythonawsrest
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OpenAI
📍 San Francisco• Full-time
2mo ago

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are looking for a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and de

awsrestai
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O
2mo ago

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are seeking a technically proficient, business-minded AI Deployment Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Solutions Architecture Lead. This role is based in Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Partner closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. Experiment and prototype alongside customers, demonstrating practical use cases. Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. Synthesize and deliver valuable feedback to the Product and Research

javascriptpythonjava
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O
2mo ago

About the team The AI Deployment Engineering (ADE) team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We act as trusted advisors and technical partners to our customers, helping them build and execute their AI adoption strategy post-sale. Our mission is to develop a strong backlog of GenAI use cases tailored to each customer’s industry and to drive these initiatives from prototype to production through hands-on technical guidance and partnership. As a Partner ADE, you’ll support systems integrators and their most strategic customers transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the role We are looking for a driven solutions leader with a product mindset as the founding Partner ADE to own the technical engagement with our systems integrators (including GSIs, RSIs, and boutique SIs) and ensure their customers achieve tangible business value with GenAI. You will help partners identify high-value use cases and provide technical enablement through the implementation of AI solutions. Your efforts will accelerate partners’ time to unlock distribution and adoption, ensuring they deliver exceptional results for our joint customers while maintaining high-quality standards. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Head of Solutions Architecture. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embed with GSIs, RSIs, and boutique SIs as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API for their customers. Work with senior SI and customer stakeholders to identify the best applications of GenAI in their industry a

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OpenAI
📍 Singapore• Full-time
2mo ago

About the Team The Consumer Products team at OpenAI builds the hardware that brings advanced AI technology directly into people’s hands. We design, engineer, and manufacture next-generation consumer devices that combine elegant design, robust engineering, and cutting-edge AI. Our team spans mechanical, electrical, and systems engineering — partnering closely with industrial design, operations, and software to create seamless, high-quality experiences that make AI more accessible and useful. About the Role As a Hardware Engineer on the Consumer Products team, you’ll contribute to the design, development, and integration of complex hardware systems for new AI-driven devices. You’ll work across disciplines to translate early product concepts into reliable, scalable, and beautifully crafted products ready for mass production. This role is based in Singapore. We follow a hybrid model (four days per week in the office) and offer relocation support for new employees. Occasional travel to manufacturing partners may be required. In this role, you will: Design, prototype, and validate mechanical and electrical subsystems from early development through mass production. Collaborate closely with design, operations, and manufacturing teams to ensure quality, reliability, and scalability. Drive DFM/DFA reviews, design iterations, and bring-up of prototype and pilot builds. Debug complex system-level issues and lead root-cause investigations and resolutions. Partner with global suppliers and cross-functional teams to ensure flawless execution from concept to launch. You might thrive in this role if you: Have 6+ years of experience in consumer hardware, consumer electronics, or advanced product development. Bring deep technical fluency in mechanical, electrical, or systems engineering (cross-disciplinary experience a plus). Have taken at least one consumer product from concept to mass production. Are energized by hands-on problem solving, iteration, and building in fast-paced enviro

awsrestai
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