Computer Systems Validation Analyst Jobs

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors, software, and data center systems that provide the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing transformative technologies. Our U.S. engineering teams contribute to the hardware and software platforms that support the next generation of AI systems. The Opportunity We are looking for a computer engineering, electrical engineering, or computer science student or recent graduate to join the BMC Development team as a Firmware Engineering Intern. You will work with experienced engineers on low-level and embedded firmware that supports the operation, control, and manageability of advanced compute systems. This internship provides hands-on experience in firmware development, test automation, engineering experiments, and lab-based system testing in a Linux development environment. You will own clearly defined technical tasks with guidance from the team and contribute to production-quality engineering work. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You Will Do Contribute to the design, implementation, and testing of system and embedded firmware. Develop and maintain firmware and supporting software in C, C++, or Python. Support firmware development and debugging in a Linux-based engineering environment. Create automated tests and scripts that improve firmware validation, test coverage, and engineering efficiency. Contribute to continuous integration and delivery workflows for firmware development and testing. Plan and conduct well-defined engineering experiments, record results accurately, and draw conclusions from test data. Support lab setup, system configuration, hardware bring-up, and firmware testing. Use debugging and diagnostic techn

Shipping the software that powers Zoox’s autonomous vehicles is an extremely challenging job. As a Software Engineer on the Core Data team, you will help build the foundational systems that capture, persist, move and retrieve the critical data generated by our fleet of robots. Our systems connect real-time vehicle software with the engineering and operational workflows requiring fleet data. This includes making critical data available for development, validation, fleet operations, incident investigation, and continuous improvement of the autonomous driving stack. You will tackle complex challenges involving high-speed data, constrained compute & storage resources, multi-host architectures, and fault-tolerant design. This role combines hands-on implementation and systems-level problem solving with opportunities to influence the long-term architecture of Zoox’s vehicle data systems. You will collaborate across the organization to define requirements and deliver practical, reliable solutions to ambiguous cross-functional problems. In this role, you will: Contribute to the technical architecture and implementation of Zoox’s on-vehicle data systems Design and develop reliable, high-performance systems for capturing, storing, retrieving, and transmitting vehicle data with strict real-time and resource constraints Own complex technical problems from initial investigation through design, implementation, validation, and rollout Collaborate across teams through requirements definition, design reviews, and code reviews Qualifications: Bachelor’s degree in computer science, engineering, mathematics, or a related field and 3+ years of professional software development experience Strong proficiency in modern C++ Experience with multithreading, concurrency, inter-process communication, or networking Strong problem-solving skills and the ability to investigate issues across multiple software and

Role Overview We are seeking a Staff Simulation Engineer to build an end-to-end aerial autonomy simulation stack at DoorDash Labs. This is a highly technical, hands-on leadership role focused on defining and implementing the simulation architecture that underpins autonomy development, validation, CI/CD testing, and pilot training. You will operate as the technical authority for simulation: owning core architecture decisions, developing key components yourself, and setting engineering standards. You will build and mentor a small, high-caliber simulation team while remaining deeply involved in implementation and system design. This role is ideal for someone who has built simulation systems from first principles, understands simulator internals deeply, and is excited to create a world-class platform from scratch. Key Responsibilities Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.. Develop high-fidelity simulation capabilities, including: Flight dynamics modeling Contact modeling and constraint handling Sensor and perception simulation Autonomy software-in-the-loop (SITL) integration Design and implement scalable simulation infrastructure to support: Regression testing in CI/CD pipelines Continuous validation of flight autonomy and autopilot software stack Mission-level testing and scenario generation Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment. Establish technical direction, architecture standards, and performance benchmarks for simulation. Mentor and grow a small team of simulation engineers while remaining deeply hands-on. Required Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field. 10+ years of experience in robotics or physics-based simulation. Deep expe

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity As a Graduate Performance Engineer, you will contribute to the design, integration, bring-up, and validation of complex server- and rack-level performance of elaborate, large-scale systems. You will work alongside experienced engineers, software developer, and cross-functional partners while building practical skills in component, system and scale up/out performance optimization and design. Start: September, 2027 Location: Austin, Texas, USA What You’ll Do Support the design, peer review, bring-up, and debug of complex server- and rack-level systems. Assist with modeling, design and evaluation of the complete software and hardware stack identifying performance bottlenecks, possible solutions and testing those outcomes. Collaborate with many different teams across both hardware and software development and testing. What You’ll Bring A bachelor’s or master’s degree in electrical engineering, computer engineering, or a related discipline, completed before the role’s start date. Equivalent relevant education or practical experience will also be considered. Foundational knowledge of software development, hardware architecture and general understanding of performance implications. Hands-on experience gained through coursework, laboratories, internships, research, student projects, or personal projects. Ability to analyze technical problems, document your work, communicate clearly, and collaborate effectively. Curiosity, sound engineering judgment, a

Zoox has embarked on a highly ambitious journey to develop a full-stack autonomous mobility solution for our cities. We’re looking for a technical program manager to drive cross-functional programs delivering our next-generation compute platform and sensor architecture — the hardware and software backbone of our autonomous vehicle stack. You'll own program strategy, execution, and risk management across hardware, embedded software, and systems integration teams, working closely with hardware engineering, perception, and platform software groups to ship on schedule. In this role, you will: Own the end-to-end program plan for next-gen compute and sensor software workstreams, from architecture definition through bring-up, validation, and production readiness. Partner with hardware, firmware, perception, and systems engineering leads to align on requirements, interfaces, and milestones across the compute/sensor stack. Identify and drive resolution of cross-team dependencies, technical risks, and schedule conflicts before they become blockers. Build and maintain program schedules, tracking mechanisms, and executive-level status reporting. Facilitate technical trade-off discussions (performance, power, cost, timeline) and drive decisions to closure with engineering leadership. Establish and evolve program management processes (planning cadences, milestone reviews, launch readiness criteria) for a fast-moving hardware-software program. Qualifications BS or MS degree in computer science, engineering or equivalent job experience 8+ years of technical program management experience, with a track record on programs spanning embedded software and hardware (compute platforms, SoCs, sensors, or similar) Strong track record of managing complex, long-running, cross-functional projects Deep familiarity with software, hardware, or automotive development processes An ability to keep the big

Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company's ability to safely and quickly iterate on autonomy development. We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines. This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred. In this role, you will: Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors Improve the ML training pipelines supporting the autonomous behavior org Qualifications Bachelor’s degree in Computer Science or related field and 8+ years of industry experience Experience optimizing large-scale distributed systems for cost and efficiency Experience with AWS or similar providers Proficiency with Python and familiarity with C++ Bonus Qu

Zoox is looking for an experienced software engineer to work on large-scale simulation pipelines used to validate the behavior of the Zoox self-driving vehicle. These are data and GPU intensive workloads built on Ray.io and Kubernetes. Given the massive scale and criticality of these pipelines, ensuring their reliability and efficiency has a significant impact on the company's ability to safely and quickly iterate on autonomy development. We are a small, scrappy team within the larger Autonomy organization. Although this role primarily involves off-vehicle pipelines, you will work closely with engineers developing the on-vehicle algorithms and models in our autonomy stack. We stay close to the end users - autonomy engineers - and think about the end to end use case for these validation pipelines. This is a hands-on role with a high degree of independence and ownership. You will be expected to contribute towards the framework’s architecture, reliability, efficiency, and grow its capabilities to support new use cases. You should have a track record of keeping production systems running with high availability. Experience with robotics or autonomous systems is not required but an understanding of the robotic data lifecycle is preferred. In this role, you will: Improve the cost efficiency, reliability, and performance of our validation and simulation pipelines Create production-grade APIs, SDKs, and tools to enable a varied set of validations of autonomous behaviors Improve the ML training pipelines supporting the autonomous behavior org Qualifications Bachelor’s degree in Computer Science or related field and 6+ years of industry experience Experience optimizing large-scale distributed systems for cost and efficiency Experience with AWS or similar providers Proficiency with Python and familiarity with C++ Bonus Qu

This role in the Offline Driving Intelligence team is responsible for developing/learning behavior models for road users such as cars, bicycles, and pedestrians. These agents populate Zoox's simulations and must be indistinguishable from real road users, yet fully controllable: promptable into the rare, adversarial, safety-critical behaviors we need to test against. This means the team’s models directly impact how fast Zoox can train, validate and ship its driving stack. Our team collaborates closely with Planner, Simulation and Validation teams to develop and validate our driving performance. As an ML Agents Machine Learning Engineer, you will work on the bleeding edge of the industry, developing novel machine learning pipelines and models to predict the behavior of other agents in the world and planning the best course of action for the ego vehicle. In this role, you will... Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like driving agents. Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism. Build generative behavior models (e.g. autoregressive, diffusion) that are conditionable on scenario intent — "cut off the ego vehicle," "jaywalk here" — for targeted stress-testing. Leverage our compute, infrastructure and large corpus of data to push boundaries of the field. Develop metrics and tools to analyze errors and understand improvements of our systems. Collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem. Qualifications PhD degree in computer science or related field and 4+ years of relevant professional experience or master's degree and 7+ years of relevant professional experience

As a Robotics Software Engineer on the Isaac Applications Team, you will bring together the software and hardware that enable Physical AI robots to operate in the real world. You will build working robotic systems and end-to-end workflows for engineers and AI agents. These workflows connect data, simulation, and real-world deployment to continuously expand and improve robot capabilities. We’re looking for strong software engineering skills, broad robotics knowledge, and enthusiasm for working hands-on with physical robots when taking ideas into practice. You enjoy understanding how components interact, solving problems across their boundaries, and seeing them come together to deliver new robot capabilities. What you will be doing: Lead the forefront of Physical AI progress in both simulated and real humanoid robots by building the humanoid reference platform that features NVIDIA's robotics technologies. Build end-to-end workflows to develop, evaluate, and deploy increasingly autonomous and interactive robot capabilities. Extend our platform to new robot embodiments and demonstrate its adaptability through hands-on integration and validation. Address real-world compute, latency, and bandwidth constraints on physical hardware. Collaborate across teams in Shanghai, America, and Europe to connect capabilities and deliver reliable robotic systems. What we need to see: Master’s degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience). 8+ years of relevant industry experience working on robotics software. Hands-on experience integrating, deploying, and testing software on physical robots, and confidence working directly with hardware when needed. Experience deploying and evaluating learned policies to control physical robots. Broad working knowledge of robotics software, hardware, AI, an

Job Title NPSS Quality Assurance Manager Job Description Job Title: NPSS Quality Assurance Manager Lead and execute compliant, risk-based assurance for computerized systems that support medical device quality and business processes. This role combines hands-on Computer System Validation (CSV), quality oversight, stakeholder leadership, and audit readiness across the system lifecycle. Focus CSV / CSA and Quality Assurance Experience 8+ years in regulated environments Work Model Office-based / Hybrid designation to be confirmed The opportunity As an NPSS QA Manager, you will own and strengthen the validation and assurance framework for non-product software and computerized systems used in a regulated medical device environment. You will partner with process owners, IT, Quality, Regulatory, Cybersecurity, Privacy, suppliers, and project teams to ensure systems are fit for intended use, compliant, inspection-ready, and maintained in a validated state. Your role Provide quality oversight and consultancy across the full computerized system lifecycle, including intended use, classification, validation planning, requirements, risk assessment, supplier assessment, test strategy, traceability, release, change control, periodic review, incident and problem management, and retirement. Develop, implement, and maintain computerized system validation deliverables, procedures, and guidance for CSV and Computer Software Assurance (CSA). Collaborate effectively with project teams and the NPSS team, consistently applying current GxP standards. Apply a risk-based, critical-thinking approach that scales assurance activities to patient safety, product qual

Job Title NPSS Quality Assurance Manager Job Description Job Title: NPSS Quality Assurance Manager Lead and execute compliant, risk-based assurance for computerized systems that support medical device quality and business processes. This role combines hands-on Computer System Validation (CSV), quality oversight, stakeholder leadership, and audit readiness across the system lifecycle. Focus CSV / CSA and Quality Assurance Experience 8+ years in regulated environments Work Model Office-based / Hybrid designation to be confirmed The opportunity As an NPSS QA Manager, you will own and strengthen the validation and assurance framework for non-product software and computerized systems used in a regulated medical device environment. You will partner with process owners, IT, Quality, Regulatory, Cybersecurity, Privacy, suppliers, and project teams to ensure systems are fit for intended use, compliant, inspection-ready, and maintained in a validated state. Your role Provide quality oversight and consultancy across the full computerized system lifecycle, including intended use, classification, validation planning, requirements, risk assessment, supplier assessment, test strategy, traceability, release, change control, periodic review, incident and problem management, and retirement. Develop, implement, and maintain computerized system validation deliverables, procedures, and guidance for CSV and Computer Software Assurance (CSA). Collaborate effectively with project teams and the NPSS team, consistently applying current GxP standards. Apply a risk-based, critical-thinking approach that scales assurance activities to patient safety, product qual

About Graphcore Graphcore is a global leader in artificial intelligence computing systems. We design advanced semiconductors and data center hardware that deliver the specialized processing power needed to advance AI while improving the efficiency required for broad adoption. As part of SoftBank Group, Graphcore belongs to a family of companies developing some of the world’s most transformative technologies. Our new AI Engineering Campus in Austin will play a central role in building the future of AI computing. The Opportunity As a Mechanical Engineering Intern, you will contribute to the mechanical design and thermal validation of advanced AI hardware. Working alongside experienced mechanical and thermal engineers, you will gain hands-on experience with 3D computer-aided design (CAD), laboratory setup, test development, prototype evaluation, and engineering documentation. Type: 12-week summer internship Timing: May - August (exact dates to be confirmed) Commitment: Full-time What You’ll Do Contribute to mechanical design activities using Creo or comparable 3D CAD software, including part modeling, assemblies, drawings, and design updates under the guidance of experienced engineers. Work with the thermal engineering team to develop test procedures and help set up laboratory capabilities for evaluating AI hardware. Support thermal and mechanical testing using appropriate laboratory equipment; collect, organize, and analyze test data. Assist the mechanical and thermal design teams with prototype evaluation, troubleshooting, design verification, and documentation of findings. Collaborate with cross-functional engineering partners, communicate progress and issues clearly, and follow applicable laboratory and safety procedures. What You’ll Bring Current enrollment in a bachelor's, master's, or doctoral program in mechanical engineering or a related discipline during the internship. Students in other disciplines with relevant mechanical engineering exper

The Research Engineer – Mechatronics is a hands-on engineering role within the TaylorMade Research & Development team, focused on the design, prototyping, integration, and validation of electromechanical systems that advance golf equipment and player performance. This role demands deep practical expertise in mechatronics, sensor systems, electronic hardware, wiring, and embedded controls, combined with the ability to develop supporting software and user-facing tools. The ideal candidate is a builder and problem-solver who thrives in a laboratory and prototype environment, producing functional systems from concept through deployment. Essential Functions and Key Responsibilities: Design, prototype, wire, assemble, and test mechatronic and electromechanical systems used in golf equipment evaluation, performance measurement, and product development Develop and interpret wiring diagrams, schematics, and electrical specifications for custom hardware assemblies, test rigs, and IoT-connected devices Select, integrate, and characterize sensors (IMUs, load cells, encoders, pressure sensors, optical sensors, etc.) – including defining operating limits, calibration procedures, and signal conditioning requirements Design and implement IoT systems and wireless data acquisition platforms that capture real-time performance data from equipment and players Develop embedded firmware and control software for microcontrollers and microprocessors (e.g., Arduino, Raspberry Pi, STM32 or similar) to drive test automation and data capture systems Write clean, maintainable code to interface with hardware, process sensor data, and build internal and user-facing applications and interfaces; leverage AI-assisted development tools to accelerate prototyping and automate test routines; apply basic computer vision techni

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron’s Design Engineering organization is dedicated to creating world‑class memory and storage solutions through sophisticated digital and analog circuit innovation. Our teams span the globe and collaborate across technology development, product design, systems architecture, and validation to deliver industry‑leading semiconductor products. The Principal Design Engineer plays a key role in developing, analyzing, and optimizing circuit designs that power Micron’s next‑generation memory technologies. This role partners closely with diverse teams—including Product Engineering, Test, Probe, Process Integration, Assembly, and Marketing—to ensure best‑in‑class performance, quality, cost efficiency, and time‑to‑market. Responsibilities: Design and optimize memory circuits from gate‑level to full chip implementations. Lead development of schematic blocks such as memory arrays, control logic, address decode, datapath, and internal test logic. Perform advanced circuit simulations using industry tools (e.g., SPICE, VERILOG) to validate performance. Drive architectural decisions related to power, speed, die area, and overall circuit performance. Collaborate with technology development and business units to define design rules, device requirements, and validation strategies. Minimum Qualifications: Bachelor’s degree in Electrical Engineering, Computer Engineering, or related technical field (or equivalent practical experience). Experience in se

JOB TITLE Data Reliability Engineer A CAREER WITH CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Ensure smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe Serve as a frontline owner for mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with investment professionals, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s REQUIRED Bachelor’s degree in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal skills. Commitment to the highest ethical standards About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Poin