Hardware Lab Manager Jobs

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: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams Build and maintain production logging, monitoring dashboards, and evaluation infrastructure Add new capabilities to the training codebase, such as long context support or novel architectures Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams Contribute to

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: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams Build and maintain production logging, monitoring dashboards, and evaluation infrastructure Add new capabilities to the training codebase, such as long context support or novel architectures Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams Contribute to

The AV Safety Software Data Engineer will play a critical role in supporting Zoox’s safety data reporting and compliance efforts. In this position, you will work with large-scale fleet data to gather, analyze, and triage events for internal safety learnings and external compliance requirements. As an AV Safety Software Data Reporting Engineer, you will operationalize defined requirements through data-driven analyses, dashboards, and workflow automations. You will implement innovative processes that are rigorous, diligent, and systematic, as well as applicable and repeatable, as Zoox continues to scale, to ensure reliable and safe operations. You will continually improve our internal data-gathering, analysis, and reporting processes and work closely with our Legal, Policy, Operations, Vehicle Engineering, Safety Design, Software, Hardware, and Communications teams to ensure a rigorous, disciplined, quantified engineering approach. A successful candidate will be able to support other Zoox safety efforts, including Operational Safety, Safety Planning, Policy, System Design, and Risk Assessment activities. In this role, you will: Create, implement, and maintain our internal and external safety data gathering, analysis, and reporting processes, and work cross-functionally with other internal organizations to ensure accurate regulatory reporting. Support the implementation of safety learnings & data programs, processes and dashboards for awareness and decision-making, including systematically ensuring representation and input from key internal stakeholders. <span style="font-size: 12pt;

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. Learn more about Privy: Privy and Stripe: Bringing crypto to everyone About the team Engineering at Privy is distinguished by: High urgency: Shipping very small iterations, very fast, to learn very quickly. Product taste: Our customers are developers, and to build effective products for them requires technical knowledge - you will often be "the PM". Security mindset: A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low latency APIs, and blockchain abstractions that are accessible to mainstream developers. What you'll do Design and build the backend systems that power wallets, identity, and onchain infrastructure at scale Create platform primitives and APIs that enable teams across Privy and Stripe to build faster Lead complex technical initiatives across architecture, data, and distributed systems Improve the scalability, reliability, and performance of our core platform Help shape our technical direction through high-leverage engineering work Who you are Minimum requirements Deep experience building and maintaining a production system at scale An understanding of mo

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. About the team Engineering at Privy is distinguished by High urgency—Shipping very small iterations, very fast, to learn very quickly Product taste—Our customers are developers, and to build effective products for them requires technical knowledge—you will often be "the PM." Security mindset—A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low latency APIs, and blockchain abstractions that are accessible to mainstream developers. What you’ll do We're looking for an exceptional Forward Deployed Engineer to join our team and be the primary technical owner for building out new capabilities with Privy's most important customers. In this role, you will combine technical expertise with a deep understanding of customer and business objectives to architect, develop, and deploy software features that address customers’ needs and evolve the capabilities of Privy’s core products. Customer obsession is a core part of Privy’s culture. You’ll work closely with fellow engineers, product, and business teams to ensure Privy's customers achieve their desired outcomes and are delighted

Why Work with Us Solve impactful problems. At Seven Research, our close-knit team unites brilliant minds passionate about pushing technological and scientific boundaries in the global markets. We provide state-of-the-art resources and cultivate intellectual freedom, enabling our people to develop groundbreaking solutions to the most complex challenges of our field. Our collaborative approach celebrates excellence from everyone, regardless of tenure. Your Role Core Developers are at the heart of our technological ecosystem, working to continuously optimize our research and technological infrastructure. In this role, you will build key components to accelerate our trading operations, design scalable systems and tools that support high-performance computing, and ensure that our systems provide the speed and robustness necessary to maintain our edge. You will be challenged to produce elegant and efficient code every day. You will also conduct in-depth research and testing relating to performance optimization, networking architecture, and hardware selection. If you are excited by the prospect of solving these sorts of problems in a collaborative, research-driven environment, we would love to get to know you. What We’re Looking For We seek talented engineers who approach problems with a holistic, innovative mindset. No financial knowledge is expected. You should have excellent programming and analytical skills and be excited to apply these talents within our state-of-the art research and trading infrastructure. You should be motivated to take ownership over core projects and always ready to identify and resolve inefficiencies. You should be continuously guided by the question: how can this work better? The ideal candidate will possess most of the following: PhD, master’s, or bachelor’s degree in computer science or a related field Strong background in data structures and algorithms, object-oriented programming, and mastery of C++ Experience with latency-sensitive developm

Who we are About Privy Our mission is to make privacy and user ownership the default online. To do so, we build simple, flexible APIs and tools for developers that make it easy to build new products on crypto rails. Privy owns the abstractions and infrastructure layer above wallets, integrating across chains, third-party providers, and Stripe products like Treasury and Link. We get to solve hard technical problems while leveraging Stripe's distribution to reach customers like Ramp, Klarna, Deel, Kraken, Hyperliquid, and Fomo — powering experiences for both mainstream users and crypto natives. Learn more about Privy: Privy and Stripe: Bringing crypto to everyone About the team Engineering at Privy is distinguished by High urgency—Shipping very small iterations, very fast, to learn very quickly Product taste—Our customers are developers, and to build effective products for them requires technical knowledge—you will often be "the PM." Security mindset—A great portion of our product is trust. While we have a dedicated security team, every engineer brings security to their designs from the start. In practice, we use boring technology like Node, React, and AWS so we can focus our engineering energy entirely on pushing the boundaries of Privy's core product, e.g. through hardware enclaves, multi-region low latency APIs, and blockchain abstractions that are accessible to mainstream developers. What you’ll do As a Fullstack Engineer at Privy, you will take on large areas of ownership in Privy’s product, architecture, and infrastructure. Because we build a developer tool, engineering and product are inextricably connected. We value intuitive interfaces, simplicity, and rapid iteration. Above all, we are building a company together to ship products that users love. Design intuitive interfaces to break down complex systems and turn them into delightful developer tooling Build and integrate systems end-to-end across client-side and server-side APIs to enable a seamle

We are seeking an experienced Backend Software Engineer to join our Crawler team. In this role, you will design, develop, and operate systems that ingest, process, and manage web-scale data in support of our next generation of advanced search technologies. This is a critical, high-impact engineering position, requiring expertise across both backend and frontend components of our data acquisition stack. Responsibilities Take ownership of and lead projects focused on developing large-scale web crawlers, ingestion pipelines, and data processing systems. Build, maintain, and optimize core backend and frontend components for crawler services, including storage, retrieval, and UI dashboards for data management. Collaborate closely with Search and Infrastructure teams to ensure the reliable, high-quality ingestion and processing of billions of web pages. Architect and implement fullstack features and scalable distributed systems that handle high-load and real-time data operations. Rapidly iterate, experiment with novel approaches, and continuously enhance system performance, usability, and reliability. Qualifications Minimum of 5 years of software development experience, with strong knowledge of data structures and algorithms in at least one of the following languages: Python, C++, Rust, or Go. Experience with large-scale web crawlers is highly desirable. Proven experience building, deploying, and optimizing high-load, distributed, and hardware-adjacent services. Deep understanding of cloud infrastructure, with hands-on experience in Kubernetes (K8s) and AWS. Demonstrated passion for writing clean, efficient, and scalable systems.

About the Role The Model Shaping team at Together AI works on products and research for tailoring open foundation models to downstream applications. We build services that allow machine learning developers to choose the best models for their tasks and further improve these models using domain-specific data. In addition to that, we develop new methods for more efficient model training and evaluation, drawing inspiration from a broad spectrum of ideas across machine learning, natural language processing, and ML systems. As a Platform Engineer in Model Shaping, you will work at the intersection of backend engineering and infrastructure, building the foundational layers of Together’s platform for model customization and evaluation. You will design, develop, and operate both the backend services and the underlying systems that enable us to sustainably and reliably scale production workflows launched by our users, as well as internal research experiments. You will operate in a cross-functional environment, collaborating with other engineers and researchers in the team to improve the infrastructure based on the needs of projects they work on. You will also interact with other engineering teams at Together (such as Commerce, Data Engineering, and Cloud Infrastructure) to integrate the services developed by Model Shaping with systems developed by those teams. Responsibilities Design and build Together’s systems and infrastructure for model customization, including user-facing features and internal improvements Contribute to reliability improvements for the platform, participating in an on-call rotation and improving processes for incident response Create and improve internal tooling for deployment, continuous integration, and observability Build a job orchestration platform spanning multiple datacenters, supporting a highly heterogeneous hardware landscape Partner with teams developing internal services, co-designing these services and incorporating them in systems built wit

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 Controller is the critical link between Nuro Driver's upstream autonomy stack and physical vehicle platform — translating planned trajectories into safe, precise, real-world motions. As a Senior/Staff Controls Engineer, you'll design and deploy production controls software that powers L4 autonomous driving across an expanding operational design domain, from parking lots to highways, in all weather and road conditions. You'll work alongside world-class engineers across autonomy, hardware, and systems to solve problems that don't have textbook answers and see your work running on real vehicles globally. About the Work Develop robust, reliable and optimized production-level control software following safety standards (ISO 26262). Develop seamless interactions between planner and controller and advanced control strategies for expanded ODD including parking lot maneuvers through highway driving under various weather condi

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We’re looking for a strong operator to carry out the testing, deployment, and logging of new advanced technologies, working outside and from various offices around the Phoenix area. Two-week training will occur in the Phoenix Arizona Area. In this role, you’ll report to the Team Lead and be a core member of our Field Operations Team. Shift: This role requires working nights and weekends, with shift hours ranging from 2 PM to 12 AM. There may be a need to rotate between shifts to support operational and business needs. There will be a two week notice provided whenever this is needed. This role requires you to be comfortable with riding an electric bike in the Phoenix Area. You will need to be comfortable biking in day/night conditions as well as in traffic/on streets. You’re excited about this opportunity because you will… Manage live tests actively in transport, deployment, and safety Work closely with multiple stakeholders to improve the product, including hardware, software, and business operations teams Execute and document tests to verify autonomous technologies, including understanding behavior, product capabilities, new and existing issues, and added requirements Rigorous attention to process, testing programs, and checklists, ensuring high levels of safety as well as efficiency and reliability of new products We’re excited about you because… 2 years of experience or strong interest in the space Drivers license required, able to support multiple locations in Phoenix, including Tempe, Mesa, Chandler, Gilbert and Scottsdale Comfortable working outside and operating micro-mobility Experience and enthusiasm with live Field Operations

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We’re looking for Forward Deployed Site Reliability Engineers who can help us build, operate, and maintain high-performance, scalable, and reliable services for our production infrastructure, primarily across on-prem environments for the US Government. Forward Deployed Site Reliability Engineers combine engineering experience and an innate drive to improve existing systems and processes, with the creativity to develop novel solutions to evolving challenges. Our team strives to automate processes wherever possible, using whichever tools are best for the job. You’ll travel to various locations where you will be the expert for Palantir’s infrastructure, helping partner teams build & configure their hardware and network for software to operate reliably within. We strongly believe in engineering teams being responsible for the operations of their services in production. In this role, you’ll work closely with engineers to advocate and participate in sensible, scalable, systems design and share responsibility with them in diagnosing, resolving, and preventing production issues. Core Responsibilities Maintaining availability of physical Linux servers that power the Palantir platform in air-gapped production environments Design, deploy, and operate infrastructure to support customer & product requirements via modern orchestration & monitoring platforms Collaborate closely with product teams on requirements & SLOs for deploying software into air-gapped environments Identifying, troubleshooting, and solving network & systems issues Scripting to automate away routine operational tasks Provide technical

The Senior Strategic Sourcing Manager will lead commercial strategy, advisory, and execution for all Zoox manufacturing projects. It will own Zoox manufacturing third-party relationships end-to-end to lead (i) competitive sourcing and negotiations, (ii) project execution, and (iii) ongoing performance of manufacturing suppliers. Finally, this role will support negotiation of capital equipment in the Zoox supply chain and also support future production strategizing. These activities ensure that Zoox’s manufacturing organizations can successfully and predictably produce complex systems at scale through world-class supplier relationships and cost structures. In this role, you will: Lead procurement and partnership initiatives for Zoox’s manufacturing organizations; build and maintain strategic relationships with key suppliers as the lead point of contact for all commercial topics Lead the day-to-day process of ensuring successful partnerships (milestone adherence, change order management, quality assurance, cost control, etc.) and build supplier performance assessments to support future sourcing decisions Proactively engage with Zoox stakeholders (incl. engineering, operations, manufacturing, strategy, finance, and design) to derive and execute the short- and medium-term business and technology roadmap to support Zoox’s vehicle assembly and service deployment Design, conduct, and synthesize supplier, industry, and market research; drive cost transparency and build total cost of ownership models to support sourcing decisions Ensure optimal contract coverage for the commodity/service in partnership with engineering and legal support Qualifications 8+ years of experience focused on commercial analysis and decisions Expertise in capital projects and equipment for hardware manufacturing/production Experience driving completion of complex projects with internal and external parties Ability to vi

About the Team OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: Design and implement inference infrastructure for large-scale multimodal models. Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. Enable experimental research workflows to transition into reliable production services. Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in t

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: Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Strong candidates may also have experience with: High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Python or Rust You may be a good fit if you: Have significant software engineering experience, particularly with distributed systems Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Want to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Representative projects across the org: D