Ai Runtime Engineer 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 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

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 ship AI products. THE ROLE As a Site Reliability Engineer at Baseten, you'll define and codify the gold standards of day 2 operations for our ML infrastructure platform. You'll envision and build robust systems, processes, automations, and observability tooling that keep our platform reliable at scale — and that empower the broader organization to operate confidently. You'll work closely with engineering, forward-deployed and product teams: learning from recurring failure patterns, turning tribal knowledge into automated mitigations, and raising the operational floor for the entire company. EXAMPLE INITIATIVES You'll work on projects like these as part of the SRE team: Improve Baseten SRE Practices, by instrumenting SLOs and SLIs, improving alerting and observability for all services. Building AI-assisted tooling for incident triage and response. RESPONSIBILITIES Own the reliability of Baseten's multi-cloud Kubernetes infrastructure, including incident response, post-mortems, and remediation tracking. Build and maintain observability infrastructure — metrics, logging, dashboards, and alerting — as code. Author, validate, and improve runbooks for recurring failure patterns, ensuring they're structured for low-context, safe execution. Identify high-frequency failure patterns and convert them into automated mitigations or self-healing automations. Diagnose and resolve runtime issues related to latency, memory behavior, GPU utilization, concu

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About The Role HP IQ is seeking a Senior Power Systems Engineer to drive end to end system architecture, modeling, and optimization for wearable platforms. The candidate will build power models, define system use cases and operating modes, partner with product and engineering teams to meet aggressive power targets, and define manufacturing tests and field telemetry for NPI. The ideal candidate brings strong systems thinking, hands-on experience with low power architectures, and the ability to build models and telemetry to drive tradeoffs from SOC level to board level to maximize user runtime. What You Might Do: Power architecture responsibility for a wearable device covering SoC states, sensor, audio, and memory architecture tradeoffs at board level. Battery, PCM, and charging profile definition and validation Design power experiments, test plans, and measurement & telemetry mechanisms across firmware and hardware to optimize power and performance. Build and maintain system-level power models to model expected power consumption for user profiles. Map power models by subsystem, correlating

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! The Interaction Design team is responsible for creating and maintaining the runtime APIs that support rich, high fidelity interactions and animations across our product suite. Our team’s work is critical to ensuring products like Prototyping, Slides, and Smart Animate have the platform needed to empower customers to bring their designs to life in new and exciting ways. The team is also responsible for building new interaction and animation-based features. In this role, you’ll lead the team that enables engineers at Figma to easily develop the next generation of interactive Figma features and products. 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: Build and execute on a long-term roadmap to improve the platform, features, and runtimes supporting interactive and animated experiences in Figma products like Prototyping and Slides Hire, manage, support and develop a team of engineers, including staff level engineers Partner with product and engineering leadership to set strategy, priorities, and mission for teams and projects Roll up your sleeves as needed to get involved in the technical details of solving some of the most complex technical challenges at Figma Establish trust within and across teams by creating accountability and a positive work environment in partnership with other leaders in the organization Grow your career in an engaged and creative engineering community Figma is committed to building an inclusi

InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our office or remotely in the United States. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 10+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering A track record of operating at Staff or Principal scope: defining technical direction, resolving cross-team ambiguity, and personally championing initiatives from conception to delivery Strong coding skills in Go (Golang), Python, C, C++, or Rust Proven track record of building and operating large-scale distributed systems or cloud platform infrastructure Hands-on experience using Terraform, CloudFormation, or Ansible for automated infrastructure provisioning Demonstrated experience owning infrastructure in Linux,

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 a software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

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 On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. Contribute to runtime improvements, compute/communication over

Who We Are At MongoDB, we are building the future of data platforms with MongoDB Atlas; our fully managed, multi-cloud database service. The Infrastructure Security (InfraSec) team sits within Site Reliability Engineering (SRE) in the CTO organization. We are an engineering team dedicated to building the security infrastructure, primitives, and reusable controls that protect MongoDB Atlas across AWS, Azure, and Google Cloud (GCP). InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our New York City office or remotely in the eastern or central timezone. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection. Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 5+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering Strong coding skills in Go (Golang), Python, C, C++, or R

Who We Are At MongoDB, we are building the future of data platforms with MongoDB Atlas; our fully managed, multi-cloud database service. The Infrastructure Security (InfraSec) team sits within Site Reliability Engineering (SRE) in the CTO organization. We are an engineering team dedicated to building the security infrastructure, primitives, and reusable controls that protect MongoDB Atlas across AWS, Azure, and Google Cloud (GCP). InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our New York City office or remotely in the eastern or central timezone. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection. Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 5+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering Strong coding skills in Go (Golang), Python, C, C++, or R

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 ship AI products. THE ROLE We're looking for an Engineering Manager to lead part of our Inference Performance team. This team makes the world's most demanding AI workloads run faster and more efficiently on GPUs. You'll manage and grow a team of inference performance engineers working across the inference engine and runtime: kernels, scheduling, batching, KV-cache management, speculative decoding and prefill/decode disaggregation. This is a hands-on technical leadership role. You'll set direction, unblock hard problems and earn the team's trust by going deep on GPU performance, while also hiring, developing and supporting the people doing the work. Your team's output directly affects how fast our customers' models run and how efficiently we serve them. The team is scaling quickly, so you'll help shape how it is structured as it grows. EXAMPLE INITIATIVES Your team will work on these types of projects as part of our Inference Runtime team: Agentic inference optimization: 50-90% faster engines Agentic Kernels in Production Live draft model training for speculative decoding The Baseten Inference Stack RESPONSIBILITIES Lead, mentor and grow a team of inference performance engineers through regular 1:1s, clear feedback, career development and performance reviews. Hire top GPU and inference engineering talent, and build a strong, collaborative team culture as the runtime team scales. Own the technical roadmap and execution for runtime performan

About the Team OpenAI Consumer Devices is building the next generation of products that bring powerful AI into people’s everyday lives. Guided by OpenAI’s mission to ensure AGI benefits all of humanity, our team combines world-class researchers, engineers, designers, and operators who care deeply about creating useful, intuitive, and responsible technology. You’ll have the opportunity to work alongside exceptional people on ambitious, zero-to-one challenges at the intersection of hardware, software, and AI. This is a chance to help define an entirely new category of products—and shape how people experience AI in the future. Our team works across silicon, embedded systems, operating systems, and cloud services to build reliable consumer devices and the novel platforms required to support them. We partner closely with research to bring advanced AI capabilities into the physical world. About the Role As an Operating Systems Engineer focused on on-device inference, you will design, develop, and ship the OS stack that makes advanced AI capabilities reliable, responsive, and energy efficient on consumer devices. Your work will span OS services and frameworks, inference runtime integration, model fitting, scheduling, and performance and power management. You’ll partner with research to adapt models to device constraints, make design decisions across the stack, and carry solutions from early exploration through integration and production. In this role, you will: Build the inference platform: Design and implement maintainable OS services, frameworks, and clear interfaces for inference execution, model loading and lifecycle, and resource management. Fit models to device constraints: Partner with researchers on quantization, runtime integration, and memory optimization to meet memory, compute, and energy budgets while evaluating model quality and product behavior. Coordinate system resources: Develop scheduling and resource policies that balance inference with other device act

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role The Embedded Software team is looking for a Frontier UX Engineer to build the software that turns design intent into interfaces people can pick up and use. You will work closely with Design, taking ideas, use cases, and specifications from early prototype through a world class shipped product, pushing the UI experience to its limit. Much of the work has no precedent, requiring comfort with unclear requirements and problems that cross design and several software layers. We care a lot about how the product feels to use, and we want someone who shares that mindset. Responsibilities Turn design specifications, use cases, and rough ideas into shipping interfaces, from early prototype through production on real hardware Own execution: take a prototype the whole way to something that ships, with the quality bar held at each step Find where the design language outruns the platform, and push the UI software at every layer needed to close the distance Advise designers on what the system is actually capable of, early enough for it to change the design Shape the UI runtime and system architecture with requirements drawn from real designs rather than hypotheticals Own the end-to-end development of user experiences alongside design, firmware, and hardw

About Mach Industries Founded in 2023, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms. At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees, we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security. The Role Mach Industries is building an AI-forward autonomy stack for contested environments where GPS and other sensing are unavailable or unreliable. As an Embedded Autonomy Engineer, you own the Linux mission computer that manages cameras, sensors, and the autonomy stack in flight. You bring up Jetson-class compute, integrate high-bandwidth cameras and sensors into Linux, and make perception, planning, decision making, and on-edge inference run in real time under real SWaP, thermal, and vibration constraints. This is a role for an exceptional embedded Linux engineer who wants to work up into the autonomy stack, not just maintain boards: kernel and camera/SerDes bring-up, the sensor-to-GPU pipeline, on-target CUDA/TensorRT runtime, and the autonomy software that sits on top. Key Responsibilities Own bring-up and lifecycle of the Linux mission computer: board support packages, device trees, kernel configuration, and bootloaders on NVIDIA Jetson/Tegra and similar SoCs. Integrate high-bandwidth sensors into Linux end to end: MIPI CSI cameras with GMSL/FPD-Link SerDes, V4L2, and ISP tuning, plus radar over PCIe or Ethernet; own time-sync and calibration across the sensor suite. Build and optimize the real-time sensor-to-GPU data path that feeds perce

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 senso

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 senso