System Performance Engineer Jobs

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! 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. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

About the Team ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The ChatGPT Infrastructure team builds and operates the platforms that enable fast iteration without compromising performance or reliability. We design shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on to ship changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that incorporate operational lessons as defaults, so engineers don’t need to rediscover failure modes, latency pitfalls, or integration issues each time they build something new. About the Role We’re hiring Senior and Staff Engineers to design and build infrastructure systems that underlie ChatGPT and multiply the effectiveness of teams building user experiences. This is not a support-only role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling to make safe, fast iteration the norm. Your work will reduce friction, prevent regressions, improve performance, and ensure systems scale gracefully as the product grows. Where You Can Have Impact You might work on one or more of the following areas (without being restricted to any single area): Platform foundations & frameworks: Core libraries, service frameworks, and shared components that standardize system building, integration, and evolution. Scalability & performance primitives: Patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand increases. Reliability guardrails: Mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and robust regression contr

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 a Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. 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: Own rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a person ready to take up the challenge of working in a high-profile project where we integrate multiple chiplets into a System-in-package, in collaboration with external stakeholders. You will work with Tenstorrent worldwide experts and leaders in the USA, Japan and other countries, and help us make our IP even better. In this role, you will ensure functionality and performance of the system. This role is based out of Tokyo, Japan and offer flexible Hybrid work style. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Responsibilities: Verify Tenstorrent’s digital IP and SoC logic at chiplet integration level, using industry standard verification methodologies Build and improve components of verification infrastructure including model builds and simulation/regression runs, Create verification components like testbenches, checkers and test generators, Add assertions and coverages along associated methodologies, Build verification test plans for subsystems, align them with project stakeholders, implement test suites, summarize the results and share feedback with project stakeholders Publish and review verification metrics and drive

MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn healthtech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really is : We are seeking a detail-oriented and technically strong AI QA Engineer to ensure the quality, reliability, and performance of Large Language Model (LLM)-based systems. In this role, you will be responsible for designing and executing test strategies, validating model outputs, and building evaluation frameworks to enhance the accuracy, safety, and overall performance of AI-driven applications.We would particularly value candidates who have hands-on experience in developing evaluation frameworks (evals) for AI systems, along with strong expertise in comprehensive system testing and quality assurance practices.You are responsible for making MeltPlan work in the real world. What You'll Do: Design, develop, and execute evaluation frameworks (Evals) for Large Language Models (LLMs) and AI syst

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role We are looking for an experienced Mechanical Engineer with 7+ years of experience in design of IT hardware from chip/package to system levels. You’ll work alongside experts in thermal, mechanical, electrical, software, and systems engineering to support the design, analysis, and validation of mechanical and thermal systems that ensure the reliability, efficiency, and longevity of mission-critical hardware. This position requires strong analytical skills, hands-on testing experience, and the ability to work in a fast-paced, cross-disciplinary 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: Lead mechanical design for AI supercomputer product in the data center application Collaborate with the cross functional team to design and optimize thermal solutions for data center hardware, including chips, power modules, and system-level cooling architectures Collaborate with cross-functional teams to integrate thermal management strategies into hardware design, from concept to mass production Design and validate mechanical systems, including chassis, enclosures, cooling systems, and high-power connections, ensuring alignment with performance and reliability standards. Perform 3D modeling, FEA, tolerance analysis, and prototyping, ensuring manufacturability and a

NVIDIA is seeking a Senior Firmware Engineer to join our CSP Engagements team, focusing on system software for Datacenter products such as GB200. This role combines deep technical expertise in embedded firmware development with customer-facing responsibilities to enable cloud service providers with next-generation computing platforms. You will work at the intersection of hardware and software, driving technical solutions from concept through deployment. What you will be doing: Design and develop firmware solutions for manageability and observability of data center servers. Actively participate in hardware bring-up activities, OOB firmware development, protocol stacks (Redfish, PLDM, MCTP, NSM) and hardware-software co-design for Cloud Service Provider deployments. Debug and troubleshoot NVIDIA GPU firmware issues, power management, performance, and thermal control problems for data center deployments, providing active support to CSPs. Partner directly with CSPs to deliver technical solutions, co-develop & co-debug features and optimizations, and provide support during new product introductions. Perform advanced system debugging, root cause analysis, and performance optimization for large-scale data center environments. Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation. What we need to see: Deep expertise in data center server architectures, HPC systems, and hardware-software co-design. Deep expertise in embedded firmware, server management controllers, and hardware bring-up with proven track record of shipping production BMC solutions Strong knowledge of DMTF protocols (Redfish, IPMI, PLDM, MCTP, SPDM), telemetry frameworks, and out-of-band management architectures Expert-level skills in C/C&

We're looking for a Senior Platform Reliability Engineer who brings strong software engineering skills and a deep understanding of system behavior under load and stress. This role is a good fit for someone who wants to own reliability as a first-class concern – building the foundational systems that protect Asana's platform, not just responding when things go wrong. You'll build core platform systems like load shedding, rate limiting, circuit breakers, and traffic controls that protect Asana under real-world load. This is deep, cross-cutting work that shapes stability and performance of our entire infrastructure – and you'll partner closely with other platform teams to make reliability something that's built in, not bolted on. Our tech stack includes: AWS, Kubernetes (EKS), CloudFront, Istio, Cilium, MySQL (RDS), OpenSearch, DynamoDB, Redis, Terraform, Datadog, TypeScript, Scala, Go, and Python. (Yeah, we know this sounds like buzzword bingo – but we want this post to actually show up in your searches.) Why this role? Reliability as a first-class feature : You won't be patching things up after the fact. You'll build the systems that make Asana resilient by design. Foundational work : Load shedding, traffic management, ingress/egress – these are the building blocks that protect everything else. You'll own them. Strong collaboration, reasonable hours : You'll work closely with infrastructure teams in Warsaw and Reykjavik, making deep collaboration practical without constant timezone gymnastics. Room to grow : This is a new team, and you'll help shape what Platform Reliability Engineering looks like at Asana – whether that means leading projects, mentoring others, or defining our technical direction. In this role, success means shipping systems that other teams rely on by default – because they make the platform safer, not because they're mandatory. We're especially interested in people who think like backend engineers but obsess over failure modes, capacity plan

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 are looking for a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. 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: Own the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and de

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. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction

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 As a software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

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

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 are seeking an experienced Optical Network Engineer to lead Laser related work within our optical interconnect efforts for large-scale compute systems. The role also requires broad, hands-on optical validation experience across IM/DD-based interconnects, working from lab characterization through production readiness and scaled deployment. In this role you will: Drive laser-focused requirements and technical direction within the broader optical interconnect roadmap. Lead evaluation and validation of optical components and subsystems, including laser-based elements, in lab and production-representative environments. Support end-to-end optical testing for IM/DD interconnects (e.g., module/system bring-up, characterization, debug, and readiness for scale). Work with external partners to align on development milestones, performance targets, and quality expectations. Own technical issue triage and resolution across performance, reliability, and manufacturability topics. Collaborate across internal teams to support integration, rollout, and operational success at scale. You might thrive in this role if you have: Strong experience in laser-focused optical engineering (development, validation, manufacturing readiness, or field support). Broad hands-on background with IM/DD optical technologies and optical test/debug workflows. Experience working with external suppliers/manufacturing partners and production-oriented execution. Demonstrated ability to debug complex t

NVIDIA is seeking a QA Engineer to join our Cloud Testing team. As part of the broader QA organization, you’ll focus on testing the software layer that enables NVIDIA’s products to achieve industry-leading benchmarks in performance and quality. This role involves hands-on testing of cutting-edge cloud and networking features, learning new technologies, and contributing to both manual and automated validation efforts. What You’ll Be Doing: Design, develop, and execute test plans for new features across software and update releases Identify and report bugs, assist in reproducing issues, and collaborate with R&D to isolate root causes and validate fixes Perform a variety of tests including functional, regression, performance, and security testing Analyze network flows and debug issues through log and system analysis Develop automation scripts and contribute to building scalable test infrastructures What We Need to See: Practical Engineer / BA / BSc in Computer Science or a related field 1–3 years of relevant work experience Proficiency in scripting and automation languages such as Python, PyTest, or Bash Strong hands-on experience with Linux systems Ability to work independently, take ownership, and execute tasks effectively Willingness and availability to work with physical lab setups Strong verbal and written communication skills in English Ways to Stand Out from the Crowd: Experience with containerized environments (Docker, Kubernetes) Familiarity with DevOps practices and CI/CD pipelines using Jenkins or GitLab Understanding and experience with Agile and Scrum methodologies A collaborative team player with a proactive and leadership-oriented minds

Key Responsibilities : Primary responsibilities :- Installation and configuration of MySQL instances on single or multiple ports. Hands-on experience of working with MysQL 5.7 and MySQL 8. Clear understanding of MysQL Replication process flows , threads , setting up multi node clusters and basic troubleshooting. Understanding of at least one of the backup and recovery methods for MySQL . Strong fundamentals of SQL and able to understand and tune complex SQL queries when needed. Strong fundamentals on the linux system side and monitoring tools like top , iostats , sar etc. At Least couple of years of production hands on experience on medium to big sized MySQL databases. Setting up and maintaining users and privileges management system and troubleshooting relevant access issues. Some exposure to external tools like Percona , ProxySQL , HAP etc. Understand the transaction flows and ACID compliance. Basic understanding of networking concepts . Performing on-call support and should be able to provide the first level support . Excellent verbal and written communication skills. Strong shell scripting skills . Good to have Python . Secondary responsibilities. :- Able to configure and setup NOSQL databases like Mongodb and Cassandra. Ability to learn new technologies along with a team and a positive outlook to understand problems from the business point of view. Qualifications: Proficiency in database management systems such as , MySQL or NoSQL databases. SQL programming and database design skills. Knowledge of database performance tuning and optimization techniques. Familiarity with database security best practices. Scripting and automation skills (Good to have- Python). Good problem-solving and analytical skills. Excellent communication and teamwork skills.