Hardware Lead Jobs

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. Basic Qualifications Proficiency in C/C++ Familiar with Sigmastar / Ambarella platform Proficiency with Video/ Audio streaming and transcoding Understanding and experience with ARM platform Experience with debuggers such as gdb, strace, etc Embedded software development experience in Linux driver and both kernel & user modes are desired Familiarity with some form of scripting (shell, python, nodejs) Familiarity with Git version control A genuine passion for embedded software development A team player, who is very self-motivated, loves difficult challenges, and is goal driven Ability to deliver on tight schedules BS/MS in Computer Engineering, Computer Science or equivalent Fluent in both written and spoken English to work effectively within a highly collaborative environment with colleagues around the world Preferred Qualifications Experience with development boards such as Raspberry Pi, Arduino, BeagleBoard Experience with build system such as OpenWRT/BuildRoot/Yocto Familiarity with standard hardware protocols (gpio, usb, uart, pwm, flash, spi, i2c, ...) Job Description In this role you will implement kernel mode and user mode applications for UniFi-Protect product line device firmware, from bootloader up to user-space applications, like Linux Kernel, rootfs, Websocket, RESTful API design, gRPC, etc You will also implement

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai

About the Team The Release Engineer team is responsible for building and maintaining the systems that power software delivery—from CI/CD pipelines and artifact management to release automation and fleet telemetry. We ensure software across bootloaders, firmware, operating systems, and cloud services is built reproducibly, validated rigorously, and released safely at scale. About the Role As a Release Engineer, you’ll design, build, and operate release infrastructure that enables reliable, secure, and traceable software delivery across complex multi-component systems. You’ll partner closely with embedded, cloud, and QA teams to ensure that every build—from development to OTA deployment—is fast, verifiable, and production-ready. We’re looking for engineers who take pride in automation, build reproducibility, and system reliability—and who enjoy building the connective tissue that allows hardware and software to ship together seamlessly. 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: Design and operate CI/CD pipelines for multi-component builds (bootloader, firmware, OS images, backend, companion apps) using hermetic toolchains. Define versioning and branching strategies; automate promotions, changelogs, and artifact retention. Integrate unit, integration, and hardware-in-the-loop (HIL) test results; quarantine flaky tests, auto-bisect failures, and block unsafe promotions. Build A/B OTA update flows with verity and health checks; run staged rollouts and canaries; implement safe rollback and roll-forward strategies. Implement code signing for binaries and firmware, generate SBOMs, run vulnerability scanning, and attach build attestations and provenance. Manage dashboards and alerts for build health, promotion latency, failure rates, and fleet update telemetry. You might thrive in this role if you: Have experience building and operating buil

Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the Role Behind the scenes, we’re a team of computer scientists, hardware engineers and experienced founders who saw a chance to make a real impact. We’re united by the challenge of building beautiful products, designed for real people—and by our commitment to using technology responsibly. We believe keeping data private and secure is core to our safety as individuals, businesses and communities and we put great care into building systems that embody our values as people. Likewise, many of Silicon Valley’s top investors believe in us: we’re backed by Sequoia Capital, FirstRound, Meritech and Siemens (Next47). What You'll Do Build, operate and improve Verkada’s Security Monitoring, Detection and Response infrastructure Onboard new systems and services to our SIEM Tune alerts to maintain high signal Automate data enrichment and incident respon

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Account Security (AccSec) pod sits within the Accounts team (part of the broader Safety organization) and is at the heart of building a safe and civil platform for users of all ages. Account Security is especially challenging at Roblox because it is open to all ages. As the EM of AccSec pod (7+ ICs) you will work closely with peers throughout Roblox and the creator community to reduce the impact of account takeover (i.e. compromise) for Roblox players, creators, and the broader community. This is a role that requires entrepreneurship. We are looking for the EM of the AccSec pod to, in collaboration with product partners, to formulate a strategy for how to reduce ATO, reduce the impact of any remaining ATO and build community trust in the security of their accounts. Examples of past and current efforts include: Cryptographically binding user secrets to hardware backed secrets. Detecting client side tampering by Browser extensions. Integration with Passkeys. Post-login modeling for ATO detection. Reducing incentives for bad actors by making assets more recoverable. While this is a security team that focuses heavily on product and infrastructure changes to improve security, we also c

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Product Design team is made up of several groups that define, create, and deliver all user-facing aspects of Stripe’s brand and product. Product Designers are strategic partners to Engineering and Product Management within their product area. In close collaboration with product teams, they shape user experiences, then translate them into high-quality designs that can be tested, shipped, and refined. Designers are responsible for building elegant, functional products that users love—and want to tell others about. The Terminal design team crafts product experiences that empower users to configure and manage in person payments. This team transforms the intricate world of payments into intuitive solutions, letting users focus on growing their businesses. The team spans hardware and software, focusing on many types of users: end users who pay at the point of sale, cashiers and operations managers who set up and run the devices, and merchants who manage a fleet of devices and need to monitor performance. What you’ll do As a product designer, you’ll work closely with the product manager and engineering team to envision payments features in the Stripe Dashboard and our end-user-facing surfaces and partner with go-to-market teams to bring them to users. That includes new feature development, product quality improvements to our most frequently used workflows, and setting vision for our products to meet new user expectations in an increasingly data

Salary Range: PLN 260,000-352,000 Subject to alignment to the responsibilities and duties of the role About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence Job Summary We are looking for a senior engineer to design and evolve an application-level simulator for ML workloads that directly influences hardware and software architecture decisions. This role sits at the intersection of machine learning, systems, and hardware design. You will model real-world workloads, predict system behaviour, and provide insights that guide how our platform evolves. Success in this role requires not only strong technical depth, but also the ability to work closely with multiple teams to ensure the simulator reflects reality and drives meaningful decisions. The Team The Tenjin team focuses on building advanced simulation capabilities to model and predict the behaviour of large-scale ML workloads on next-generation hardware and software platforms. We operate at the intersection of machine learning, systems, and architecture, developing tools that enable data-driven decisions long before systems are fully built or deployed. Our work helps shape both hardware and software direction by providing early insights into performance, scalability, and efficiency. The team brings together engineers with backgrounds in simu

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinking with the ability to understand problems across hardw

About the role As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform. Responsibilities Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones. Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value. Product Feedback Loop: Directly influence our software and model roadmap by surfacin

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role You will be a fundamental and experienced member of the Service Operations team at DoorDash Labs. You will complete more advanced diagnostic and repair work to maximize uptime, supporting our overall fleet utilization goals. You will report to the Associate Operations Manager, Service, in our DoorDash Labs organization. This is an on-site role with expectations of 100% in-office in Fremont, CA, San Jose, CA, or Sunnyvale, CA. You’re excited about this opportunity because you will… Execute any Senior Service Technician task and: Diagnose complex, intermittent, or unusual faults in robotic systems, modular components, and support vehicles, often requiring advanced troubleshooting techniques and interpretation of complex data Perform advanced repairs, including component-level troubleshooting and fixes on intricate electrical systems, control units, and associated hardware, with minimal supervision Interpret complex technical manuals, schematics, and diagnostic flowcharts to guide troubleshooting efforts Meticulously document complex diagnostic processes, root cause hypotheses, non-standard troubleshooting steps, repair details, and component failure information in the service management system, contributing potential updates to the knowledge base Provide technical guidance, mentorship, and on-the-job assistance to Level 2 Technicians for challenging tasks Work independently to manage and prioritize assigned workload effectively Calibrates, configures, and maintains specialized diagnostic tools and test equipment We operate 7 days a week, 16 hrs a day to support Robot Operations. During training, you will be on a temporary schedule until your on-the-job training is completed

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job / Role Summary The Staff Engineer drives unit process development and module execution for advanced NAND dry etch, owning defined process levels and delivering robust process solutions that meet program, yield, and manufacturability targets. Success requires deep process fundamentals, disciplined DOE/SPC execution, and strong cross-functional influence to solve complex structural challenges and enable process transfer. Main Responsibilities Develop/optimize dry etch processes to meet physical/structural and electrical requirements for advanced NAND products. Improve process capability by reducing variability and driving cost/process margin improvements. Lead root cause / failure mode analysis for process/hardware limitations and drive vendor/supplier engagement for solutions.

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. Key Responsibilities Customer-First Quality Validation Think and test like a real customer – validating how the product behaves in practical usage scenarios, not just whether it meets spec. Simulate real-world usage across different environments, clients, and edge cases to ensure the system meets expectations in performance, reliability, and ease of use. Identify and flag friction points in product workflows, even if they technically work, to advocate for an improved user experience. System-Level QA Ownership Perform full system validation from initial setup, configuration, and protocol testing to firmware upgrade and long-term usage simulation. Own both manual and semi-automated testing processes with a strong focus on integration, data consistency, and robustness across releases. Validate UI/UX flow intuitiveness and ensure management features align with enterprise users' expectations. QA Lab Setup, Maintenance & Continuous Improvement Plan, build, and maintain a dedicated QA lab environment tailored for NAS system testing—including test racks, network configurations (1G/10G), multiple client OS setups, UPS and power fault simulations, and various drive types. Set up and manage test inventory including hardware units (e.g., UNAS Pro variants), disks (HDD/SSD), cables, and switches to simulate real-world deployment scenarios

About the Team Our team analyzes inference stack performance across the application, model, and fleet layers to identify bottlenecks and drive faster, cheaper inference. We combine systems profiling, benchmarking, and analysis to understand where time and cost are spent, then turn that understanding into performance optimizations and models that project performance and capacity needs for future launches. About the Role In this role, you will model inference performance across application, model, and fleet layers with higher fidelity. You will build cost-to-serve estimates from microbenchmarks and create tools that help cross-functional teams reason about latency, capacity, utilization, and cost tradeoffs. In this role, you will Build and refine performance models that translate microbenchmark results into cost-to-serve estimates. Analyze inference workloads end to end across applications, models, and fleet infrastructure. Enhance tooling to identify bottlenecks across layers for latency and throughput. Partner with other teams to turn performance insights into concrete improvements and project how future changes affect inference. You might thrive in this role if you: Enjoy reasoning from first principles about distributed systems, model inference, and hardware efficiency. Are comfortable working across abstraction layers, from application behavior to kernels, accelerators, networking, and fleet scheduling. Have deep expertise with performance profiling, benchmarking, analysis, and optimization. Enjoy collaborating with engineering and research teams to improve real production systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve o

Zoox is looking for a manufacturing test engineer to be responsible for manufacturing testing of our sensors and ECUs used in our autonomous vehicle. In this role, you will be developing automated tests for critical components, including but not limited to lidars, cameras, radars, telematics, HV modules, sensor pod accessories, etc. You will work cross-functionally with our electrical engineering and software teams to develop and test new products and technologies. We are looking for an engineer who is curious, enthusiastic, and not afraid to embrace new technologies! Ability to work independently as well as organize work around schedules and critical deadlines is a definite plus. In this role, you will: Build, release & support test solutions for use on the manufacturing lines at Zoox and at contract manufacturing partners Develop testing scripts to verify functionality, control test instruments, capture test parameters, and analyze results for continuous improvement Implement adequate test coverage across all phases of manufacturing (PCBA, module, system, vehicle) through collaboration with other teams Release updated test programs for new generations of hardware and software Establish best practices and drive continuous improvement on test deployment, runtime, and yield Qualifications: BS in electrical engineering, computer engineering, computer science, physics, or equivalent technical degree 5+ years of relevant experience Strong knowledge of Python and shell (bash) scripting Strong knowledge of testing and troubleshooting complex electronic assemblies in a manufacturing environment Experience in developing automated manufacturing tests on Linux. Ability to debug failures using commands in the terminal Experience working with contract manu