Systems Research Engineer Intern Jobs

By submitting your resume, you’re expressing interest in our 2027 RDSS (Research and Development Substitute Services) program. Please confirm your eligibility with the local district office before applying the role. NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — 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 are looking to grow our company, and grow our teams with the smartest people in the world. What you’ll be doing: You will work with ground breaking technologies for the Tegra SoC and various NVIDIA embedded platforms Implement power and thermal management software features in Linux Kernel and user space Collaborate with power architects, hardware and software engineers on usecase power estimation, power and performance optimization What we need to see: MS in CS, CE, EE, Systems Engineering or related software/hardware engineering major Software development experience with a significant focus on Linux Excellent C programming/debugging skills within Linux kernel and user space software Background with working on embedded systems and ARM processor specific System-level debugging experience and problem-solving skills Excellent communication skills Ways to stand out from the crowd: Experience in working with the Linux and open-source software communities Understanding of the Linux power management features (scheduler, dynamic frequency scaling, runtime power management, su

Radar Systems Engineer (Experienced, Lead, Senior) Company: The Boeing Company The Boeing Defense, Space & Security (BDS) team is seeking a Radar Systems Engineer (Experienced, Lead, or Senior) to join the team in El Segundo, CA. The Space, Intelligence & Weapons Systems Engineering Team creates the next generation products and services for the BDS business unit. We work with proprietary customers to development the next-generation technologies in space. Our group works all facets of engineering from technology investment, concept development, proposal writing, requirements and design, build, integration, test, and demonstration of products in their relevant environments. The Radar Systems Engineer will be a part of a high-performing team that are immersed in high intensity development projects. As a member of our team, you will have the opportunity to design, develop, and deliver state-of-the-art communication systems for space-based applications for commercial, civil and/or national security programs. This position will work with a highly-motivated team that works with domestic customers on their latest satellite systems. Project assignments typically span the complete program life cycle, from internal trades, concept studies and system definition, to satellite development, launch, and on-orbit operations and test. Additional opportunities available and associated with this role support new business development, research and development, and rapid space technologies. Primary Responsibilities: Design, develop, and analyze next generation space-based radar payloads Define payload requirements and document payload interfaces Support conceptual hardware development reviews <

About the Team OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. About the Role We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. 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 to new employees. In this role, you will: Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. Design and iterate on user-facing tools and backend services to support high-quality data workflows Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal r

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. Would you like to work in one of the most complex Fab environments in the world? As an industrial engineering intern in our research and development factory you will work on projects that further optimize our very automated factory. This role will provide exposure to larger data sets than you have ever worked with and will challenge your data management skills. Not only will this role significantly grow your skills but will also provide exceptional value to the organization on a real issue in our factory! Responsibilities: Identify key performance indicators for R&D program success. Use large data sources to extract and analyze planning data. Build reporting in Tableau and other systems to convey data to program teams. Construct infographics that display key information in easy-to-understand formats. Leveraging AI tools and find new ways to apply AI in the workplace. Minimum Qualifications: Working towards completion of a Bachelor’s or Master’s degree in the following areas: industrial engineering, manufacturing engineering, supply chain, Operations or other related discipline with expected graduation after this internship timeframe Must be a current student, and cannot graduate prior to September 2027. Ability to code in SQL, Python or similar to execute data extraction. Effective with Excel, Tableau or other data management and visualization software. Preferred Qualifications: Skille

About the Team The Intelligence and Investigations team seeks to rapidly detect and disrupt abuse in AI technologies to ensure their safe use. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits all of humanity. About the Role As an Intelligence Systems Engineer, you’ll be focused on advancing our Intelligence & Investigations efforts at OpenAI, ensuring the safe and responsible use of AI across our products and services. We are seeking a self-starter to prototype, develop, and maintain new tools and processes that integrate OpenAI’s models and infrastructure to enable internal teams to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. You will be a crucial technical bridge between our data scientists and subject matter experts and technical teams like Platform Integrity, Safety Systems, and Research by leading the development of innovative tools and processes that bolster goals in scaled collections, investigations, and analysis. The ideal candidate has strong analytical and data skills, with a background in both prototyping and building scalable systems that can swiftly detect emerging threats, process vast amounts of information, and deliver insights to stakeholders. We value professionals with outstanding communication skills, a commitment to continuous learning, and who are dedicated to promoting the responsible use of AI. 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 to new employees. In this role, you will: Prototype, build, and maintain at-scale intelligence systems that detect, triage, and monitor targeted signals from both open-source and internal data Analyze requirements and deliver end-to-end solutions that address

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are looking for Software Engineers to join our team. This is a specialized, high-impact role sitting at the intersection of high-performance computing (HPC) and Large Language Model (LLM) engineering. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work. RESPONSIBILITIES Benchmarking : Evaluate, run and automate standard LLM quality benchmarks (GSM8K, MMLU) alongside custom performance suites for specific workloads (e.g., long-context window, KV cache reuse, disaggregated serving). DevEx Improvement : Develop and maintain internal GPU-enabled development environments (similar to GitHub Codespaces). You will ensure the team has seamless, high-performance "dev machines" optimized for model experimentation. Tool Development : Build and contribute to open-source tools such as InferenceMAX and genai-bench to automate model evaluation, benchmarking and analysis. System Profiling : Use profilers like PyTorch Profiler, NVIDIA Nsight Systems and py-spy to collect performance profiles, identify bottlenecks, and debug the compute/networking stack. Monitoring & Observability : Develop real-time dashboards and alerts to monitor system health, model startup times, and runtime performance. Continuous Integration : Automate performance

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

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 Everpure (formerly Pure Storage) is hiring a Senior Pre-Sales Systems Engineer to support our Higher Education business, with a focus on R1 research universities. R1 institutions are not one customer. A single campus can behave like a dozen different organizations at the same time: central IT running enterprise applications, research computing and HPC teams, genomics and imaging cores, AI and machine learning labs competing for GPU time, an academic medical center with its own rules and its own budget, and faculty groups buying infrastructure directly with grant money. Decisions move through CIOs, research computing directors, principal investigators, sponsored programs offices, procurement, and consortium contract vehicles, often in parallel and not always in agreement. That environment rewards someone who can hold a lot of context at once, translate between very different audiences, and connect technology to the outcomes these institutions actually care about: time to result for researchers, compliance with sponsor and grant requirements, data that stays usable for a decade or more, and budgets that have to stretch further every year. You will be the technical lead on these accounts, working alongside account managers, specialists, and partners to build solutions customers can defend internally, both technically and financially. Location: MD / VA WHAT YOU'LL DO Develop a real understanding of what drives

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 Everpure (formerly Pure Storage) is hiring a Senior Pre-Sales Systems Engineer to support our Higher Education business, with a focus on R1 research universities. R1 institutions are not one customer. A single campus can behave like a dozen different organizations at the same time: central IT running enterprise applications, research computing and HPC teams, genomics and imaging cores, AI and machine learning labs competing for GPU time, an academic medical center with its own rules and its own budget, and faculty groups buying infrastructure directly with grant money. Decisions move through CIOs, research computing directors, principal investigators, sponsored programs offices, procurement, and consortium contract vehicles, often in parallel and not always in agreement. That environment rewards someone who can hold a lot of context at once, translate between very different audiences, and connect technology to the outcomes these institutions actually care about: time to result for researchers, compliance with sponsor and grant requirements, data that stays usable for a decade or more, and budgets that have to stretch further every year. You will be the technical lead on these accounts, working alongside account managers, specialists, and partners to build solutions customers can defend internally, both technically and financially. Location: MA / NY / PA WHAT YOU'LL DO Develop a real understanding of what drives ea

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: We’re looking for a senior engineer to help build, maintain and evolve the training framework that powers our frontier-scale language models. This role sits at the intersection of large-scale training, distributed systems, and HPC infrastructure. You will design and maintain the core components that enable fast, reliable, and scalable model training — and build the tooling that connects research ideas to thousands of GPUs. If you enjoy working across the full stack of ML systems, this role gives you the opportunity and autonomy to have massive impact by working on projects such as: Building a high-performance data loading and caching pipeline. Implementing performance profiling across the ML systems stack Developing internal metrics and monitoring for training runs. Building reproducibility and regression testing infrastructure. Developing a performant fault-tolerant distributed checkpointing system. Key Responsibilities: Build and own the training framework responsible for large-scale LLM training. Design distributed training abstractions (data/tensor/pipeline parallelism, FSDP/ZeRO strategies, memory management,

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. We validate Micron memory products on current and next-generation computing platforms. As an Intern System Compatibility Engineer, you will join our System Enablement and Test Development teams and gain hands-on experience with platform bring-up, system configuration, memory validation, test development, automation, data analysis, and AI-enabled engineering workflows under the guidance of experienced engineers. We will provide technical mentorship, structured onboarding, and exposure to DRAM, BIOS and firmware interactions, computer architecture, laboratory workflows, responsible use of approved AI tools, and the memory product lifecycle from initial bring-up through qualification and readiness. Key Responsibilities Set up and support Intel, AMD, and ARM-based systems in Linux, Windows, and UEFI environments; document hardware, BIOS, firmware, operating system, memory, and test configurations for repeatable execution and traceability. Implement memory validation activities that assess compatibility, stability, reliability, performance, and platform readiness. Reproduce and triage failures, collect logs and diagnostic data, use issue-tracking systems, apply structured failure-analysis methods, and support validation of corrective actions. Build or refine automation using Python, PowerShell, C&#43;&#43;, or related languages; use approved AI-assisted tools to accelerate code development, test generation, log analysis, data summarization, technical research, documentation, and report

About the Team The mission of the Applied AI Engineering team is to enable the secure and impactful implementation of Agentic solutions. In this international Government role, you will deliver clearly scoped AI use cases with public-sector customers, from a mission need through hands-on implementation, architecture, evaluations, measurable adoption, and documented handoff. Account-aligned technical and commercial owners retain ongoing account ownership. About the Role We are looking for a driven solutions leader with a product mindset to partner with our international public-sector customers and ensure they achieve tangible value with GenAI. You will pair with government agencies, policymakers, and other public institutions to establish a GenAI strategy and identify the highest value applications. You’ll partner with their technical teams, subject matter experts, regional cloud providers, systems integrators, and implementation partners to move from prototype through production. You’ll design architectures using supported OpenAI technologies and approved services, with explicit data, inference, evaluation, and production-readiness boundaries. You will collaborate closely with regional Sales and Solutions Engineering, Global Affairs, Applied Research, Product, Legal, and Security teams. This role is based in London. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deliver clearly scoped technical implementations with sophisticated international public-sector customers, serving as their hands-on engineering partner to build applications on supported model APIs, Codex, and other approved OpenAI technologies. Work with senior customer stakeholders to identify the best applications of GenAI in their industry and to build/qualify a comprehensive backlog to support their AI roadmap. Intervene directly to accelerate customer time to value through building hands-on prototypes and/or by deliv

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. Job Summary We are seeking a motivated engineer to join the DRAM Systems Engineering team, focusing on the development, evaluation, and optimization of next-generation memory systems for AI accelerators. This role emphasizes research and development across hardware architecture, operating systems, and performance analysis to support Agentic AI inference workloads. If you are ambitious and eager to make an impact in the exciting world of AI and memory systems, this is the perfect opportunity for you! Responsibilities Characterize AI inference workloads and examine memory behavior Build and evaluate tiered memory hierarchies for AI accelerators Study KV cache lifecycles, MoE models, and data placement strategies Compare and optimize explicit versus hardware-assisted data movement Develop, test, debug, and detail system-level and OS components Prototype and evaluate agentic AI systems by building agents and multi-agent workflows using modern frameworks and orchestration patterns (planning, tool use, memory, and context management). Apply these technologies both as workloads under study and as accelerators for internal engineering workflows <h2 style="color:!importan

Software Engineer Build technology where every nanosecond matters. At Graviton, software isn't just a tool that supports trading. It is the infrastructure behind every research breakthrough, every trading decision and every competitive advantage. As a Software Engineer , you'll work on systems where performance, reliability and precision matter at an extraordinary scale. You'll partner closely with software engineers and quantitative researchers to build technology that processes enormous volumes of market data, powers quantitative research and supports live trading. You'll take on problems that don't have obvious answers — from designing high-performance systems and distributed infrastructure to eliminating bottlenecks measured in microseconds and building tools that make our researchers and engineers faster. Your work will go into production, be measured against real-world performance and have a direct impact on how our trading systems operate. If you enjoy solving hard engineering problems, understanding systems at a deep level and pushing technology to its limits, you'll feel right at home. What You'll Work On You'll work across the engineering stack that powers our quantitative research and trading platforms. Depending on your team, your work may include: Designing and building high-performance, low-latency systems in modern C++. Building distributed systems that process and analyze massive volumes of market data . Designing systems where latency, throughput and reliability directly influence trading performance . Working on Linux systems, networking, concurrency and multithreaded applications. Profiling systems, identifying bottlenecks and optimizing performance at the hardware and software level. Building robust infrastructure that supports quantitative research and live trading. Debugging complex production systems and solving problems where correctness and reliability are critical. Designing internal platforms and developer tools that accelerate research an

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. Role Overview We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without hurting performance Work within existing low-latency architecture instead of fighting it Profile and remove bottlenecks rather than guessing AI for Engineers & Researchers Build tools that genuinely speed up research and development Improve code understanding, review workflows, and internal knowledge retrieval Keep systems auditable and predictable LLM & Retrieval Systems Implement structured RAG and embedding pipelines with validation in place Create safe integration layers between models and internal systems Performance & Standards Track latency, drift, and stability — not just accuracy Build observability into everything you ship Help raise the bar for how AI is engineered here What We’re Looking For Strong Python fundamentals Clear thinking around system design and performance trade-offs Experience deploying AI systems in production (1–5 years is typical) Familiarity with transformers, embeddings, or LLM deployment Nice to have: Exposure to C++ / Rust / Go E