Ai Deployment Manager Jobs

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our team is growing and we are looking for experienced machine learning researchers and engineers to join us. In this role, you will apply your expertise in machine learning to solve an array of challenges in Nuro's autonomy stack — detection with sensor fusion, tracking, fine grained classification, human intent understanding, to name a few. About the Work You will be involved in all stages of problem solving, including initial proof of concept, model iteration, onboard deployment, and on-road performance monitoring and troubleshooting. You will develop techniques and/or processes that allow us to train models that are able to utilize massive scale of data, but still keep the model onboard latency in check so that it is deployable. You will have the opportunity to take a novel problem, assume the ownership, and just go deep on it. About You Recent experience in applying state-of-the-art deep learning techniques to solving auton

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Team The Devices Platform team's mandate is to lay the foundation of Nuro's onboard software for our sensor and compute platform, including device drivers, inter-device protocols and pipelines, and device runtime APIs. Sensors and compute hardware are the eyes, ears, and brains of our self-driving robots. We are creating the hardware-agnostic platform to be used by the perception and autonomy SW stack, and to realize the full potential of our sensor and compute HW in reliability, quality, and performance. The projects we work on are high impact and high visibility within Nuro. This team is also responsible for working with internal stakeholders and external suppliers to define, evaluate, integrate the next generation HW platform for Nuro's products and to build the necessary tooling to assist continuous testing and validation. About the Work Design and develop sensor and compute systems for robotics Architect and/or deploy Nuro

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors About the Role Evaluation Infrastructure plays a critical role at Nuro, directly enabling L4 driverless deployment. The team supports two demanding workloads: day-to-day Autonomy Evaluation that powers rapid software iteration, and large-scale Driverless Safety Validation that produces the rigorous evidence required to deploy autonomy on public roads. The Evaluation Infrastructure team builds the metrics framework, evaluation pipelines, introspection tooling, and analysis products that turn raw on-road and simulation logs into actionable insight. Our metrics stack spans both heuristic and ML-based approaches, covering everything from low-level component accuracy to end-to-end behavior quality. The platform empowers autonomy and Systems & Safety teams to run complex evaluations and validations across a wide range of configurations and scales, producing the high-fidelity metrics that drive both short-term iteration and long-term release

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models. Develop and maintain continuous testing and monitoring systems for core ML infrastructure components. Develop observability to track ML model lifecycles from data generation to on-road validation. Maintain an in-house ML inference platform to serv

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The Autonomy ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Optimize Nuro’s autonomy stack with cutting-edge optimization techniques like quantization, low precision inference, and model pruning. Work with autonomy engineers to optimize, validate, and deploy large language models. Develop and maintain a world-class model compiler framework, FTL . Write robust, high-quality software to increase our confidence in our vehicl

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The Autonomy ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Optimize Nuro’s autonomy stack with cutting-edge optimization techniques like quantization, distillation, and model compression. Work with autonomy engineers to optimize, validate, and deploy large language models. Develop and maintain a world-class model compiler framework, FTL . Write robust, high quality software to increase our confidence in our vehicle

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The mandate of the learned behavior team is to use advanced machine learning techniques to accelerate software progress. In this role, you will work closely with the software vertical teams to understand their pain points and explore novel and advanced machine learning methods to solve practical real-world challenging problems. To name a few, using self-supervised learning to learn robust representations, exploring techniques for out-of-distribution detection to solve long tail problems, adjusting reinforcement learning techniques for motion planning, working on trajectory prediction and motion planning, investigating the robustness of models to mitigate uncertainties, or trying to build an end-to-end driving system. If you love solving challenging new problems with a mindset of deriving practical solutions to eventually be used on the vehicle, come join us! About the Work Work on scalable machine learning based planning and pre

The Application Modernization Platform (AMP) team is tackling one of the industry's most critical challenges: leveraging Generative AI to transform rigid, legacy applications into modern, microservices-based architectures powered by MongoDB. We are building a comprehensive, SaaS-like platform, encompassing both the "brain" (multi-agent reasoning and orchestration) and the "hands" (the deployment platform and modernization toolset). This solution requires a robust platform foundation and infrastructure designed for a "build once, run anywhere" model, ensuring seamless operation regardless of a client's security or network constraints. A key challenge is balancing the need to tune our tools for each customer's unique tech stack and restrictive environments with making them easily extensible and scalable for common application modernization challenges. We seek an engineering leader for this high-visibility initiative. This role requires defining the high-level strategy and technical direction across all AMP engineering pillars, leading the execution of solving uniquely complex application modernization puzzles, and delivering an enterprise-grade product. The leader will minimize deployment friction, meet customer compliance requirements, and help shape the future of how global enterprises leverage GenAI. The ideal candidate is a hands-on technical leader who excels at leveraging GenAI capabilities, architecting complex distributed systems, and designing the orchestration agents necessary to reliably and fluidly run the entire software development lifecycle. This role will be based in North America's West Coast (PST), and offers a hybrid working model. The ideal candidate for this role will have 10+ years of software development and operations experience, with a focus on building platforms and distributable software infrastructure Deep experience in building data warehouses and core components for data processing systems Have experience in using GenAI in building comple

The Application Modernization Platform (AMP) team is tackling one of the industry's most critical challenges: leveraging Generative AI to transform rigid, legacy applications into modern, microservices-based architectures powered by MongoDB. We are building a comprehensive, SaaS-like platform, encompassing both the "brain" (multi-agent reasoning and orchestration) and the "hands" (the deployment platform and modernization toolset). This solution requires a robust platform foundation and infrastructure designed for a "build once, run anywhere" model, ensuring seamless operation regardless of a client's security or network constraints. A key challenge is balancing the need to tune our tools for each customer's unique tech stack and restrictive environments with making them easily extensible and scalable for common application modernization challenges. We seek an engineering leader for this high-visibility initiative. This role requires defining the high-level strategy and technical direction across all AMP engineering pillars, leading the execution of solving uniquely complex application modernization puzzles, and delivering an enterprise-grade product. The leader will minimize deployment friction, meet customer compliance requirements, and help shape the future of how global enterprises leverage GenAI. The ideal candidate is a hands-on technical leader who excels at leveraging GenAI capabilities, architecting complex distributed systems, and designing the orchestration agents necessary to reliably and fluidly run the entire software development lifecycle. This role will be based in North America's West Coast (PST), and offers a hybrid working model. The ideal candidate for this role will have 10+ years of software development and operations experience, with a focus on building platforms and distributable software infrastructure Deep experience in building data warehouses and core components for data processing systems Have experience in using GenAI in building comple

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We're looking for an Optical Interconnect System Engineer to design, qualify, and deploy scalable optical connectivity for large-scale AI infrastructure. This role spans fiber-system architecture, optical-mechanical integration, validation, reliability, deployment, and serviceability. You will work with optical, mechanical, electrical, networking, manufacturing, reliability, and data-center teams to translate system needs into practical interconnect solutions. This is a hands-on role for someone who can connect design decisions with installation, qualification, troubleshooting, and long-term operational performance. In this role, you will: Define optical interconnect architectures and requirements across hardware platforms and rack-level systems. Design high-density fiber systems for performance, density, reliability, installation, and serviceability. Lead optical-mechanical integration and cross-functional design reviews. Develop test and qualification plans for optical components, modules, switching platforms, and integrated systems. Own optical loss budgets, routing guidelines, handling requirements, and serviceability criteria. Support system bring-up, deployment, troubleshooting, failure analysis, and reliability improvement. Create reusable design guidelines, interface requirements, and qualification methods. You might thrive in this role if you have: Core experience Experience desi

About the Team The Enablement Lead (EL) 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 EL team accelerates time-to-value, deepens product adoption, and helps make OpenAI indispensable to how organizations work. About the Role The Enablement Lead, Builder role is a specialist post-sales technical enablement role focused on delivering high-impact enablement and adoption services across OpenAI’s product suite. You will design and deliver technical learning experiences covering OpenAI APIs, Codex, agents, evaluations, and related platform capabilities. You will work with engineers, AI and platform teams, administrators, security stakeholders, product leaders, and executive sponsors. 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, helping customers progress toward production use, and turning lessons from individual engagements into resources and practices that benefit many customers. This role is based in our San Francisco HQ. 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 technical enablement of OpenAI products, including OpenAI APIs, Codex, Agents, Evaluations a

About the Team OpenAI’s Business organization works with customers and partners on some of our most complex and consequential opportunities. These efforts require rigorous strategy, strong operating leadership, and coordinated execution across commercial, product, technical, deployment, and go-to-market teams. About the Role We are hiring a Business Lead to serve as the operating leader for a strategically important initiative anchored in a major partnership. This person will turn an ambitious, cross-functional mandate into a clear strategy, operating plan, decision structure, and set of measurable outcomes. This role combines strategy and operations, product judgment, commercial skills, and the ability to get things done. You will identify the most promising product and customer opportunities, develop a point of view on how our products should work together, shape the commercial approach, and personally drive execution across both organizations. This is a hands-on role for someone who wants to own outcomes, not just coordinate work. You will structure ambiguous problems, establish priorities, build trusted relationships with internal and external stakeholders, and work across product, engineering, deployment, and go-to-market teams to remove blockers and deliver results. Success means establishing a durable operating model for the initiative, improving decision velocity, translating strategy into coordinated execution, launching a joint go-to-market motion, landing an initial cohort of customers, and delivering a high-quality enterprise deployment. In this role, you will: Own the initiative’s integrated strategy and operating plan, including priorities, desired outcomes, metrics, owners, dependencies, and decision points Structure complex and ambiguous business problems, develop fact-based recommendations, and translate them into clear choices and executable plans Define success measures and build operating reviews that surface progress, risks, tradeoffs, and requi

About the Team The Monetization team is a new cross-functional group spanning engineering, product, research, and design. We are building the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to create user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen trust, expand economic opportunity, and support OpenAI’s long-term innovation. We believe monetization should deliver clear user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem for developers and businesses. The team operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment. We partner closely across Product, Design, and Research to bring new capabilities into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build the integrity systems that keep OpenAI’s ads products safe, trustworthy, and resilient to abuse. In this foundational role, you will design infrastructure that detects and prevents harmful, deceptive, fraudulent, or policy-violating ads and advertiser behavior at scale. This role is well suited to an engineer who has built large-scale systems in ads integrity, trust and safety, anti-abuse, fraud, security, risk, or a related domain—and who wants to apply that experience in an ambiguous 0→1 environment. You will work across risk signals, detection and enforcement platforms, review tooling, adversarial resilience, advertiser controls, and integrity measurement. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You will collaborate with Ads Delivery, Ads ML, Product, Research, Safety, Policy, Privacy, Legal, Security, and operations teams to create a high-integrity ads ecosystem from first principles. This role is based in San Francisco. We offer relocation assistance t

About the Team OpenAI is evaluating multiple infrastructure pathways, including powered land, colo/BTS, and NeoCloud opportunities. The Site Readiness & Development team provides the diligence layer needed to compare opportunities, identify risk, and support credible deployment decisions across those pathways. About the Role The NeoCloud & Colo Due Diligence Lead will evaluate third-party infrastructure opportunities where OpenAI is considering deployment through NeoCloud, colo, or BTS structures. This role will focus on facility and deployment readiness, including MEP readiness, rack strategy, developer capability, facility design, power deliverability, schedule credibility, and operating assumptions. Unlike the land diligence team, this role is centered on technical and operational readiness of third-party infrastructure rather than greenfield site master planning, civil development, and entitlement strategy. This is an individual contributor lead role and does not have direct reports initially. The role determines whether each opportunity is fit-for-use and fit-for-service against OpenAI facility, rack, power, network, reliability, and operational standards; identifies material deficiencies and tracks remediation with developers/operators; and evaluates commissioning, validation, AHJ/code, and deployment interfaces such as structured cabling, network readiness, and high-density rack support where relevant. Key Responsibilities Lead diligence on NeoCloud, colo, and BTS opportunities across technical and operational readiness dimensions. Assess each opportunity against OpenAI facility, rack, power, network, reliability, and operational standards to determine deployment fit. Validate MEP readiness, rack deployment strategy, facility design assumptions, power deliverability, and schedule credibility. Identify material deficiencies and work with developers/operators to define remediation plans, owners, timing, and residual risk. Review reliability, availabilit

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role Forward Deployed Engineers lead complex deployments of frontier models in production. You will embed with customers where model performance matters, delivery is urgent, and ambiguity is the default. You will use this to map their problems,You will use this to map their problems, structure delivery, and ship fast. You will scope, sequence, and build full-stack solutions that create measurable value. You will also drive clarity across internal and external teams. You will identify reusable patterns and share field signal that influences the roadmap. Success in this role means owning the delivery state across workstreams. You will hold the bar on quality and pace and help OpenAI learn through execution. This role is based in Abu Dhabi. 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 will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they c