Zoox
Senior Staff/Principal Software Engineer - GPU System Software, Onboard Execution
Be an Early Applicant
Lead the architecture and strategy for onboard GPU execution in Zoox autonomous vehicles. Define GPU scheduling, multi-tenancy, isolation, deterministic latency, compute budgets, hardware selection, and inference performance direction. Drive end-to-end reductions in latency, utilization, power, and cost across models, runtimes, middleware, and hardware. Provide technical leadership, mentor senior engineers, align cross-functional teams, and lead platform bring-up and performance optimization.
Zoox is building a purpose-built robotaxi from the ground up and running it on public roads today, with riders. Every perception, prediction, and planning decision runs on an onboard compute: a fixed-power, fixed-thermal, safety-critical, real-time system.
That makes GPU execution one of the most consequential engineering problems in the company. Each new model generation wants more compute. Each new vehicle generation needs to cost less, use less power, and stay safe. Closing that gap is not a kernel-tuning exercise. It takes an end-to-end technical vision for how the whole onboard AI workload is scheduled, shared, isolated, and sized across GPUs, and the authority to drive that vision across ML, autonomy, middleware, and hardware organizations.
You will join Zoox's Software Performance organization, which owns end-to-end performance of the onboard software stack: profiling and observability, GPU compute, and compute platform. You will work closely with Perception, Prediction, Planning, ML Infrastructure, and Hardware teams, and you will be a senior technical voice for onboard compute across the company.
We are looking for the technical leader who sets that vision. You will define how Zoox runs AI on the vehicle, and you will own the strategy for doing more with less compute on every vehicle we build next.
In this role, you will:
- Architect onboard GPU execution. Define how perception, prediction, and planning workloads share onboard GPUs, including scheduling, multi-tenancy, isolation, and deterministic latency under contention.
- Drive compute reduction. Own the multi-year roadmap to cut onboard compute per vehicle by setting latency and utilization budgets and landing the biggest levers across models, runtimes, middleware, and hardware in real releases.
- Shape hardware and platform direction. Guide next-generation compute decisions (GPU and SoC selection, topology, memory budgets) with workload models and performance projections that justify them, then lead performance bring-up of each new platform.
- Lead inference performance at scale. Set direction for the inference stack (TensorRT, CUDA, custom kernels, quantization) and partner with ML teams so models are designed for the hardware they ship on.
- Provide technical leadership. Lead and mentor senior engineers, align directors and VPs through design docs, and make the hard calls when performance, safety, and schedule conflict.
Qualifications
- BS in computer science, computer engineering, or related field and 10+ years in systems or performance engineering, including leading GPU or accelerator architecture across teams, or building and leading a performance engineering team.
- Deep CUDA platform (programming model, runtime, and driver) and NVIDIA GPU microarchitecture expertise (Ampere through Blackwell, Orin, Thor).
- Proven record setting technical direction and delivering large, measurable end-to-end gains in latency, utilization, or cost.
- Working knowledge of ML inference optimization (TensorRT, XLA, Triton, quantization, fusion) and expert C++ on Linux.
- Ability to align ML, systems, hardware, and leadership on a shared technical plan.
Bonus Qualifications
- Real-time or embedded GPU experience: autonomy, robotics, AR/VR, games, or HPC.
Production GPU multi-tenancy (MPS, MIG, priority streams).
New GPU architecture or platform bring-up, benchmarking methodology, or workload modeling and projections.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Follow us on LinkedIn
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
Zoox Seattle, Washington, USA Office
1111 3rd Ave, Seattle, WA, United States, 98101
Similar Jobs
Cloud • Information Technology • Security • Software • Cybersecurity
Leads and develops a regional sales engineering team supporting Zscaler’s core and generative AI portfolio. The role includes recruiting, mentoring, scaling discovery and proof-of-concept processes, partnering with sales and customers on solution design, and driving value-based selling. Candidates need cybersecurity and networking expertise, sales or systems engineering experience, team leadership skills, AI fluency, and the ability to operate in a matrixed go-to-market environment.
Top Skills:
Artificial IntelligenceCoding AssistantsCybersecurityGenerative AiLarge Language ModelsNetworkingSaaSSaseZscaler Zero Trust Exchange
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Directs strategic PMO services across managed-services portfolios, overseeing project prioritization, governance, resource allocation, transformation delivery, executive reporting, client relationships, business development, process improvement, and leadership development. The role manages complex programs, drives technology-enabled delivery practices, coaches project leaders, and aligns portfolio outcomes with organizational goals and professional standards.
Top Skills:
ClarityConfluenceJIRAPlanview
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Leads healthcare payer data science and modernization initiatives, developing predictive models, statistical analyses, and scenario-based insights from claims, reimbursement, utilization, and member experience data. Directs multiple analytical workstreams, advises executive clients, guides cross-functional teams, supports transformation roadmaps, and promotes responsible AI use. The role also shapes thought leadership, business growth, operational improvement, and delivery quality across payer advisory engagements.
Top Skills:
Artificial IntelligenceEpicFacetsNascoOracle OhiPredictive ModelingStatistical Analysis
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
