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
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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
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us—that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale—from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Work Drive the system-level safety architecture and requirements for the Autonomy Hardware and Firmware of the Nuro Driver, ensuring compliance with automotive safety standards such as ISO 26262 and ISO 21448. Decompose vehicle-level Safety Goals into a cohesive Functional Safety Concept (FSC) and refine it into a detailed Technical Safety Concept (TSC), defining system-level safety mechanisms, fault detection and reaction strategies, and safe states. Develop the system-level SOTIF specification for the Autonomy Hardware and Firmware of the Nuro Driver, defining performance targets and acceptance criteria for safety-critical systems like Autonomy Sensors and Compute. Lead, perform, and review system-level safety analyses, including Hazard Analysis and Risk Assessment (HARA), Failure Mode and Effects Analysis (FMEA), and Fault Tree Analysis (FTA), Dependent Failure Analysis (DFA) to identify risks and deriv
About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Responsibilities (What he/she will do after joining UI) - Own system-level DQA and validation activities for Energy Storage System (ESS) products throughout the NPI lifecycle. - Develop test plans and qualification criteria for ESS reliability, functionality, performance, safety, and system integration. - Validate ESS architectures, including battery packs, BMS, PCS/inverters, EMS, power distribution, protection circuits, and grid interaction. - Perform system integration testing for charge/discharge, grid-connected operation, backup power, load transitions, power outages, and recovery scenarios. - Define and execute reliability validation, including temperature, thermal cycling, humidity, vibration, ESD, surge, and long-term operation. - Validate BMS protection mechanisms, including over/under-voltage, over-current, short-circuit, temperature protection, SOC/SOH, and cell balancing. - Validate PCS/Inverter performance, including conversion efficiency, load response, abnormal operating conditions, and protection mechanisms. - Conduct high-power and thermal validation for battery cells, connectors, terminals, busbars, relays/contactors, and other high-current paths. - Conduct failure analysis (FA), root cause investigation, and corrective action verification for NPI, reliability, and field/RMA issues. - Apply FMEA/DFMEA, MTBF, sta
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
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 The Pure Engineering Team builds the industry’s most innovative, high-performance, and highly available portfolio of products that are designed for the most demanding mission critical applications. Our customers are the most important part of our business and they love our products for its simplicity of management, the constant flow of new and exciting upgrades, and ability to live on the cutting edge of technology while never taking downtime, ever. These new innovations enable our customers to leverage the agility of the public cloud for both traditional IT and cloud-native applications. WHAT YOU'LL DO Responsible for debugging Hardware and System level issues Lead Hardware and Mechanical validation of new drive designs, both internally and with JDM. Includes board level signal/power measurements, mechanical testing, thermal measurements, 4-corner testing, etc… Support interoperability and debug of Pure Storage devices in customer systems Analyze and document test results Perform failure and root cause analysis to support field issues, customer escalation and factory defects Collaborate with cross-functional teams to implement corrective actions and process improvements We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave. WHAT YOU BRING 7+
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, hands-on RTL engineer with deep packet-networking and interconnect expertise to own critical on- and off-chip communication components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip fabrics connecting high-bandwidth compute, memory, and I/O subsystems, as well as purpose-built off-chip interfaces and protocols that enable custom computing at scale. The ideal candidate has recently owned production RTL for networking or packet-switched datapaths such as Ethernet switches, NICs, SmartNICs, network accelerators, RDMA/RoCE systems, NoCs, or custom scale-up/scale-out fabrics. This is a senior engineering role with broad technical ownership and substantial direct RTL work. You will drive designs from requirements and performance analysis through microarchitecture, SystemVerilog implementation, verification closure, physical design convergence, silicon bring-up, and production readiness. You will also plan and oversee the work of junior engineers and help develop productive engineering relationships with external partners. In this role, you will: Own the microarchitecture, RTL design, and delivery of major packet-based interconnect and networking components, including NoC fabrics, switches, routers, bridges, protocol adapters, arbiters, queues, schedulers, buffers, and traffic-management logic. Design mechanisms for routing, arbitration, ordering, flow con
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
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 seeking a Software Driver Developer to create reference drivers for our AI-IP in a reference system. You will also support our AI-IP customer optimizing our reference driver into our customer specific systems. This role is hybrid, based out of Belgrade, Serbia. 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. Who You Are Deep systems engineer with 7+ years of experience in device drivers or low-level systems programming. Strong proficiency in C and C++ with a solid understanding of hardware-software interfaces. Hands-on experience developing Linux kernel drivers, including kernel architecture, debugging, and kernel-space/user-space interactions. Experience developing drivers for high-speed I/O or interconnect technologies such as PCIe; PCIe driver development is strongly preferred. Familiar with user-mode and kernel-mode driver models and understands that Linux kernel driver development differs meaningfully from bare-metal or RTOS-based driver development. What We Need Design and evolve the driver layer that provides high-performance APIs for Tenstorrent devices. Develop and maintain user-mode and kernel-mode drivers for Te
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 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
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 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
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
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