Computer Systems Validation Analyst Jobs

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

About Zoox Zoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a driverless future. Our mission is to make transportation safer, more sustainable, and accessible to everyone. At Zoox, innovation, collaboration, and a bold vision for the future drive everything we do. About Our Part Time Student Worker Program Zoox’s program offers hands-on experience with cutting-edge technology, mentorship from some of the industry’s brightest minds, and the opportunity to make meaningful contributions to real projects. We seek part time student workers who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox’s mission. Project Overview Zoox is seeking a motivated Firmware Engineer student worker to join our team, focusing on diagnostic services for the thermal and body systems. This is an opportunity to own highly-visible, foundational projects where you will extend our existing diagnostic infrastructure. You will work on the full development cycle of robot firmware development. In this role, you will: Work on the development of diagnostics for autonomous vehicle software, ensuring robust fault detection, reactions, and serviceability Design, develop, and test embedded software for body, thermal, lighting, and door functions of the Zoox vehicle Contribute to all phases of the software development cycle including prototyping, requirements capture, design, implementation, and validation Collaborate with system, software, hardware, and test engineers to define, implement, and validate diagnostic requirements Qualifications: Currently enrolled in a Bachelor's or Master's program in computer science, computer engineering, electrical engineering or equivalent experience Proficiency in modern C++ for firmware development Experience with Python programming Experience with embedded micro-control

About the Job Turn complex AI workload signals into faster, more efficient systems at data center scale. As a Senior AI Performance Engineer, you will analyze and optimize AI training and inference workloads across large-scale distributed systems. Your work will connect compute, memory, communication and software behavior. You will own complex performance investigations from problem definition through validation. You will turn profiling, benchmarking and modeling results into improvements engineers can build from. You will design benchmarks, investigate system bottlenecks and optimize distributed communication software across technologies such as MPI, NCCL, UCX and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale deployment. This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to own complex technical work and coo

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. About the Role We are looking for Staff System Software Engineer in Test to join our team. In this role, you will be responsible for design, development, automation and reporting of Integration and system tests spanning across firmware and device drivers. This role requires you to have significant technical breadth and deep understanding of low-level system software specifically in server class systems. You will be part of a new team responsible for integration of different system software deliverables and development of system tests spanning all the components. You will contribute to shaping the test strategy , guide best practices and solve complex problems while maintaining a strong hands-on focus. You will partner with development and other QA teams to deliver high quality scalable and reliable solutions. About the Team Integration and system test team is responsible for verification and validation of integrated components across Board management controller (BMC), Firmware and Linux device driver. The team is also responsible for management and maintenance of common tools and pipel

The Onboard Behavior Model Architecture team is responsible for developing deep learning models that leverage data and compute at large scale to train driving models. We learn and predict behaviors from large scale expert data and large scale reinforcement learning to produce a ML driver that is safe, comfortable, and completes the mission. In this role, you will collaborate closely with the Onboard Perception, Cost Planner, Simulation, Validation, Data Science, Systems Engineering, QA, and ML Infra teams. In this role, you will: Lead a Team: Manage, mentor, and grow a team of individual contributors, fostering a culture of innovation and continuous improvement. Develop Strategy: Develop and organize our overall strategy for Onboard Behavior ML Models for generating driving plans for our autonomous vehicle. You will interface with multiple partner teams to identify opportunities for model improvements within their problem area. You’ll be setting the short and long term technical direction for the team and collaborate on broader company-wide directions. Provide technical guidance and leadership in the design and development of training models at large scale and work with partner teams on ensuring their efficient inference. Monitor Performance: Establish and monitor key performance indicators (KPIs) to measure the effectiveness of work packages and drive continuous improvement. Manage Resources: Manage the allocation of resources within the team, ensuring that projects are staffed appropriately and that team members have the necessary tools and support to succeed. Qualifications Expertise with Reinforcement Learning and Machine Learning for at least one of these areas: Planning, LLMs, VLAs/VLMs, recommendation systems. Extensive experience with programming and algorithm design, strong mathematics skills. MS or Ph

About Graphcore At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. Job Summary We are looking for an experienced System Level Test Engineer to join our Product Test and Diagnosis Department (PTD). In this role, you will lead the development and deployment of System Level Test (SLT) solutions for next-generation AI processors. Working closely with cross-functional teams, you will contribute to the design and implementation of SLT hardware, software, automation, and characterization solutions that support silicon bring-up, yield learning, manufacturing readiness, and production deployment. The ideal candidate will possess strong technical depth in semiconductor test and validation, a passion for solving complex engineering challenges, and a strong focus on product quality and manufacturability. The Team The Product Test and Diagnostics team’s role is to detect and manage hardware defects that arise from the manufacture and use of our products. This covers chips, boards and finished systems and takes place both in the manufacturing sites and in the field. Responsibilities and Duties Lead development and deployment of SLT hardware and software solutions supporting silicon bring-up, charac

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 As a Principal Software Engineer, you will help define and build the high-performance, highly reliable foundation of the Nuro Driver. This role spans Device Platform, Performance, and Onboard Systems, requiring deep technical leadership across sensor and compute integration, onboard runtime systems, distributed execution, and autonomy software performance. You will architect hardware-agnostic device interfaces, inter-device communication pipelines, runtime APIs, and onboard software platforms that enable Nuro’s autonomy stack to run safely and efficiently across current and future vehicle platforms. You will also lead system-wide performance and reliability efforts, including latency reduction, resource efficiency, observability, automated validation, and tooling for debugging complex onboard systems. This is a highly cross-functional and high-impact role. You will partner with autonomy, hardware, safety, validation, opera

Senior: PLN 260,400 - 352,200 Subject to alignment to the responsibilities and duties of the role About the job Build quality foundations for Kubernetes systems that power next-generation AI compute. As a Senior QA Engineer , you will validate the workload management stack for new AI accelerator hardware. You will help ensure that Kubernetes integrations are reliable, scalable and ready for production use. Your work will support how accelerators are scheduled, orchestrated and used across distributed environments. You will test systems that make complex AI compute infrastructure dependable for real users. You will design and develop automated test suites, build system and integration tests, and contribute to improving CI/CD quality practices. You will also investigate and debug issues across Kubernetes, infrastructure and application layers. This role is for someone who enjoys hands-on technical testing, automation and working close to complex distributed systems. This is a hybrid position, with at least three days each week in our Gdańsk office. The team and culture You will join the Workload Management team, working closely with software engineers, infrastructure specialists and other QA engineers. The work is practical, systems-focused and based on strong technical ownership. Quality is built early here, not checked only at the end. You will contribute to test strategy, validation planning and automation practices throughout the development lifecycle. The team works through open technical discussion and evidence-based decisions. You will be encouraged to speak up on quality risks, improve test coverage and help turn complex systems into reliable products. As a senior member of the QA team, you will also support less experienced engineers through technical guidance, code reviews and sharing good testing practices. What we’re looking for Strong Python programming experience, with a focus on automation and test engineering Hands-on experience with Robot Framework or

Own the end-to-end execution that takes NVIDIA DRIVE Autonomous Driving Software (NDAS) from product definition to production deployment across major OEM vehicle lines. We are seeking an accomplished engineering execution leader to lead adaptation, integration, validation, and production readiness of NVIDIA Autonomous driving solution (NDAS) for strategic automotive OEMs. You will work between NVIDIA product and engineering teams and the OEM's vehicle, software, systems, and validation groups. The role involves converting an agreed feature set into a deliverable vehicle program. This entails clarifying requirements, coordinating interfaces and responsibilities, setting the engineering plan, building consistent productization workflows, and managing issue resolution. You will influence teams such as systems engineering, autonomous-driving development, platform software, functional safety, cybersecurity, quality, validation, release, and customer engineering. What You'll Be Doing: Lead NDAS execution with major OEMs across the full program lifecycle — from feature definition and technical alignment through vehicle integration, validation, launch, and production ramp — owning the coordinated engineering plan per vehicle line, including requirements, architecture, adaptation scope, achievements, staffing, validation strategy, release criteria, and production-readiness gates. Translate OEM vehicle requirements and use cases into clear commitments for NVIDIA teams, while ensuring OEM partners understand product capabilities, constraints, assumptions, and the work required on their side; build scalable, repeatable workflows for adapting NDAS to specific OEM platforms, vehicle architectures, sensor configurations, compute platforms, networks, and development processes. Drive multi-functional implementation across autonomous-driving features, systems, platform software, vehicle integratio

About the Team The Consumer Devices team at OpenAI builds end-to-end hardware and software systems that bring AI into the physical world. We work at the intersection of custom silicon, embedded systems, operating systems, cloud services, mechanical engineering, electrical engineering, and product design to deliver reliable, production-ready devices at scale. Within Consumer Devices, Hardware Engineering eXperience, or HEX, is a new bootstrapped team building the environments, applications, compute, product-data systems, and workflows that let hardware engineers do their work without needing to troubleshoot the machinery underneath. HEX owns virtual engineering environments, HPC/GPU compute, storage, networking, licensing, MCAD/ECAD/CAE applications, PLM, product data, automation, validation, and support as one connected system. About the Role As a Staff PLM & Engineering Applications Engineer, you will be one of the first technical builders of HEX and the primary counterpart to the HEX lead. You will own the engineering-application and product-data side of the hardware engineering experience, with an initial focus on NX, Teamcenter, licensing, parts import, integrations, packaging, validation, and user workflows. This is not a traditional Teamcenter administration role and not a Corporate IT application-support role. You will take complex, fragile workflows and turn them into reliable engineering systems. This role is highly hands-on and systems-oriented. You will not inherit a mature environment and support queue. You will help build a fresh one, replacing manual setup guides, tribal knowledge, repeated support issues, and team handoffs with tested automation and reliable workflows. In This Role, You Will Own the technical architecture, deployment, configuration, integration, validation, and long-term operation of NX and Teamcenter. Build reliable workflows for parts import, product-data migration, metadata quality, BOMs, revisions, lifecycle states, and releas

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking an experienced Staff UEFI Engineer to design, develop, and deploy UEFI-based firmware for Graphcore’s hyperscale AI server platforms. This role focuses on developing system firmware responsible for platform initialization, hardware configuration, and reliability features across large-scale data center deployments. The Team Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. The Firmware Engineering team develops the foundational firmware responsible for platform initialization, hardware configuration, and system reliability across Graphcore’s AI compute infrastructure. The team collaborates with silicon engineering, hardware design teams, BMC firmware teams, validation engineers, and platform arch

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. 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. Key Responsibilities Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. Translate vendor specifications into expected real-world performance for AI workloads. Evaluate architectural aspects including: compute throughput and utilization memory systems (HBM, cache hierarchies, bandwidth constraints) data types and precision tradeoffs (FP16, BF16, FP8, etc.) interconnect and scaling behavior. Run benchmarks and profiling to validate hardware performance a

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des