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 You will work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit
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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 We’re looking for an experienced systems software engineer to help define and build the host software stack for our custom next-generation AI systems. You will work close to the hardware on performance-critical software, including Linux kernel drivers, high-throughput I/O paths, and system-scale networking and RDMA. This role spans architecture, implementation, platform bring-up, debugging, and performance optimization. You will work across hardware and software boundaries to make new systems usable end to end, from low-level device interfaces through userspace tooling and production validation. In this role you will: Design, implement, and debug host-side systems software for AI infrastructure, including Linux kernel drivers and supporting userspace components. Build and optimize software paths for high-throughput, low-latency communication, including RDMA and related networking functionality. Develop software around PCIe, DMA, NICs, accelerators, memory movement, and device interaction. Bring up new hardware platforms and diagnose complex issues across kernel, firmware, networking, and hardware boundaries. Build tooling for integration, testing, diagnostics, observability, qualification, and performance characterization. Collaborate with hardware, networking, and platform teams to define interfaces and integrate new capabilities. Work with external vendors where needed to integrate technologies and drive issues to resolution. Contribute across the systems sof
NVIDIA is looking for a Systems & Software Engineer interested in building and running reliable large scale infrastructure platform services. In this role you will create and support automation that manages infrastructure, as part of our organization running EDA platforms atop of NVIDIA hardware. What you’ll be doing: Design, build, deploy, and run infrastructure services & manage the software life cycle in scope to meet our business goals Build and maintain automation to eliminate manual toil and scale output without scaling effort Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy Practice sustainable blameless incident prevention and incident response while being a member of an on-call rotation Consult with and provide consultation for peer teams on systems design best practices What we need to see: BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience Experience coding in Python and/or Go. Note : you must be able to produce code without AI assistance during the interview process. Experience with infrastructure automation and distributed systems design Experience developing tools for running large scale private or public cloud systems in production In depth knowledge of Linux systems and Containers A track record showing a good balance between initiating your own projects, convincing others to collaborate with you and collaborating well on projects initiated by others. <
We are inventors, builders, and doers, passionate and purposeful in the work we do. We have a once-in-a-century opportunity to reinvent personal transportation—and we need your help. As a Systems Integration Engineer for the Manufacturing Test and Diagnostics Engineering team, you will be part of the team that designs, develops, and executes systems and processes related to ECU and vehicle bringup, validation, testing, and troubleshooting. You will help build the next-generation infrastructure and process for testing electrical components, including hardware and firmware, on the Zoox vehicles in Manufacturing. In this role, you will: Design, develop, integrate, deploy, and support tester hardware, test software, and production equipment automation for testing at Manufacturing, supplier end-of-line (EOL), and fleet service. Build test solutions relying on Python (or other higher-level programming language) knowledge and experience with communication protocols (CAN, LIN, ETH) Build intuitive user interfaces using development skills such as React, Tkinter, or others that interface with middleware over API, TCP/UDP, Pub-Sub protocols, or other services. Serve as the first line of defense for electrical and functional issues during testing and other EOL processes, including but not limited to software/firmware, harness, networking (CAN, LIN, Automotive and Standard Ethernet, GMSL, etc.), hardware, and infrastructure issues. Work closely with multidisciplinary engineers to collect and interpret component- and vehicle-level requirements and translate them into scalable system-level validation test scripts and test cases for the vehicle integration process. Design and implement novel test solutions for future manufacturing lines and next-generation diagnostic architectures to support higher-volume production Document test solution hardware and sof
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. As a Principal Systems Software Engineer in the Storage and Memory Systems (SMS) group within Micron’s ITP Pathfinding organization, you will architect, design, and develop software that enables and demonstrates the value of future memory and storage technologies. You will work in a small, highly skilled engineering team, collaborating closely with AI/ML application and modeling specialists, software engineers, hardware engineers, and system architects. Your pathfinding work will accelerate the development of future products and influence technical direction. This role requires broad technical expertise and a willingness to contribute across multiple layers of AI and systems software stacks, from AI applications to hardware/software interfaces. Responsibilities Design and modify AI inference software stacks to enable proof-of-concept hardware capabilities. Develop software to quantify and demonstrate the value of proposed system features. Lead software architecture and development efforts, both independently and as a technical lead for small teams. Research emerging AI software topics to identify memory and storage system challenges and opportunities. Develop and modify Linux applications and libraries using C, C++, Python, Rust, CUDA, and/or SYCL for advanced heterogeneous computing systems. Develop and use emulators to predict system‑level performance and functional impacts in advance of hardware availability. Debug system-level issues spanning applications, libraries, o
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. As a Principal Systems Software Engineer in the Storage and Memory Systems (SMS) group within Micron’s ITP Pathfinding organization, you will architect, design, and develop software that enables and demonstrates the value of future memory and storage technologies. You will work in a small, highly skilled engineering team, collaborating closely with AI/ML application and modeling specialists, software engineers, hardware engineers, and system architects. Your pathfinding work will accelerate the development of future products and influence technical direction. This role requires broad technical expertise and a willingness to contribute across multiple layers of AI and systems software stacks, from AI applications to hardware/software interfaces. Responsibilities Design and modify AI inference software stacks to enable proof-of-concept hardware capabilities. Develop software to quantify and demonstrate the value of proposed system features. Lead software architecture and development efforts, both independently and as a technical lead for small teams. Research emerging AI software topics to identify memory and storage system challenges and opportunities. Develop and modify Linux applications and libraries using C, C++, Python, Rust, CUDA, and/or SYCL for advanced heterogeneous computing systems. Develop and use emulators to predict system‑level performance and functional impacts in advance of hardware availability. Debug system-level issues spanning applications, libraries, o
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. The Role As part of the Core Products Business Unit (CPBU) Systems Software team, you will join a high-leverage engineering initiative dedicated to transforming upgrade workflows and lifecycle operations. Our goal is to shift hardware upgrades from manual, support-intensive workflows toward a safer, guided, automated self-service experience integrated directly into Pure1 and Skyline. In this role as a Systems Software Engineer (MTS3), located on-site in Santa Clara, CA, you will build dedicated systems infrastructure and controller-upgrade automation for our next-generation upgrade framework. You will bridge on-array software execution with cloud-guided operations, eliminating manual choreography and runbooks while maintaining uncompromising standards for safety and availability. What You'll Do Design & Build Upgrade Infrastructure: Architect, implement, and maintain high-reliability systems software components for controller-upgrade automation and the next-generation hardware upgrade framework. Automate Upgrade Workflows: Transition complex hardware replacement and upgrade tasks into repeatable, self-service workflows, significantly reducing support and field dependencies. Engineered Safety & Resilience: Build robust state machines, health checks, workflow orchestration, pre/post-upgrade validations, failure-handling mechanisms, and automated recovery paths. Cross-Functional Collaboration: Partner closely with int
Role Overview As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. This internship is based on-site at our San Francisco HQ, running through the Winter term from January to April. Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details:&n
Role Overview As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details: Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading en
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. The Systems Integration team is critical in this mission, turning complex hardware-software development into reliable product signals. We validate complete device experiences across software, cloud services, connectivity, accessories, and real-world operating environments, combining hands-on system testing, structured test development, hardware-in-the-loop environments, diagnostics, and automation to uncover issues that component-level testing alone cannot reveal. About the Role As a Systems Test Engineer, End-to-End Validation , you will design and execute end-to-end testing for complex device experiences spanning hardware, software, connectivity, cloud services, and accessories. You’ll translate product behavior and real-world use cases into structured, reproducible test procedures and build test environments that allow failures to be reliably reproduced and diagnosed. You’ll also identify opportunities to automate repetitive or high-value scenarios, working with engineers to turn complex manual workflows into scalable validation systems. Because this is a new category of devices, you’ll have the opportunity to build the end-to-end validation foundation early—shaping test coverage, environments, and workflows from prototype through launch. We’re looking for someone who combines strong systems thinking, hands-on testing skills, technical curiosi
About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b
About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b
About the Role As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competi
NVIDIA’s invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. Are you ready to change the next generation of computing? Join us at the forefront of technological advancement. NVIDIA data center systems have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. These platforms bring together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA Networking, NVIDIA Data Center CPUs, and a fully optimized NVIDIA AI and HPC software stack. We are seeking an excellent Senior System Engineer to work on bring up, integration, validation and troubleshooting for compute tray platforms of GPU Racks — ensuring servers are fully functional and validated as per requirement before mass deployment in data centers. What you’ll be doing: Working with a global team of architects and developers on NVIDIA AI server system (CPU, GPU, Memory, NIC, PCIe, NVMe SSD, Cooling, etc.) designs. Working closely with hardware teams to influence hardware system design, reviewing schematics and board design to ensure speed of light execution. Using simulation and emulation to left-shift early design and initiate new concepts and innovations. Hands on debug and support of early server prototypes bring-up and power on test debug in datacenter system labs. Factory and Manufacturing support: Support manufacturing flows, firmware updates, and diagnostic procedures. Ensure BOM change signoff and proc
Mission Systems Integration Engineer Company: The Boeing Company The F/A-18 Mission Systems Team is seeking a Mission Systems Integration Engineer in China Lake, CA to join the Naval Air Warfare Center-Weapons Division team with a focus on developing cutting edge engineering solutions to continue to advance the fighter at the heart of the US Navy’s air wing. As a Mission Systems Integration Engineer, you will be responsible for developing engineering solutions for the F/A-18 Super Hornet and EA-18G Growler, including both enhancing existing field units with the addition of new capabilities as well as architecting and testing completely new systems. In this role, you will be joining a cross-functional team to progress our products through the development lifecycle. Tasks include developing requirements to support customer needs, creating test plans to ensure requirements are performing, and supporting lab and ground tests in an integrated Boeing/US Navy development team. Position Responsibilities: Work with customer teams to develop and document complex electronic and electrical system requirements Analyze and translate requirements into system, hardware, and software designs and interface specifications Develop test plans to test system requirements and system of systems performance Perform lab and ground tests to ensure system designs meet operational and functional requirements Provide support of fielded hardware and software over the entire product lifecycle Track risks/issues/opportunities, tools, and technology readiness Basic Qualifications (Required Skills and Experience): Bachelor of Science degre
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