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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting onboard GPU execution for AI workloads, with a focus on scheduling, multi-tenancy, and performance optimization. Proven ability to lead technical teams, mentor engineers, and make critical decisions balancing performance and safety.
Highest-signal resume keywords
Technical Leadership of Onboard GPU ExecutionExpertise in Scheduling and Multi-TenancyExperience with TensorRT and CUDAAbility to Lead Performance Bring-UpKnowledge of GPU and SoC Selection
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
GPU SchedulingDeterministic Latency StrategiesCompute ReductionCustom KernelsQuantizationPerformance OptimizationInference Stack DirectionMemory Budget ManagementAI Workload ManagementMiddleware Integration
Soft Skills
LeadershipMentoringTechnical Decision-MakingCollaborationCommunication
Industry Keywords
Onboard ComputePerformance Bring-UpAI WorkloadsVehicle HardwareDesign Documentation
About the role
Key responsibilities & impact- Architect onboard GPU execution for perception, prediction, and planning workloads
- Define GPU scheduling, sharing, multi-tenancy, isolation, and deterministic latency strategies
- Own the multi-year roadmap to reduce onboard compute per vehicle
- Set latency and utilization budgets and deliver compute improvements across models, runtimes, middleware, and hardware
- Guide next-generation GPU and SoC selection, topology, and memory-budget decisions
- Lead performance bring-up for each new compute platform
- Set direction for the inference stack using TensorRT, CUDA, custom kernels, and quantization
- Partner with ML teams to design models for vehicle hardware
- Lead and mentor senior engineers
- Align directors and VPs through design documents
- Make technical decisions when performance, safety, and schedule conflict
Requirements
What you’ll need- Technical leadership of onboard GPU execution and AI workloads
- Expertise in scheduling, multi-tenancy, isolation, and deterministic latency under contention
- Experience driving compute reduction across models, runtimes, middleware, and hardware
- Knowledge of GPU and SoC selection, topology, and memory budgets
- Experience with TensorRT, CUDA, custom kernels, and quantization
- Ability to lead performance bring-up of new compute platforms
- Ability to lead and mentor senior engineers
- Ability to align directors and VPs through design documents
- Ability to make decisions balancing performance, safety, and schedule
Benefits
Comp & perks- Paid time off, including sick leave, vacation, and bereavement
- Unpaid time off
- Zoox Stock Appreciation Rights
- Amazon Restricted Stock Units (RSUs)
- Health insurance
- Long-term care insurance
- Long-term and short-term disability insurance
- Life insurance
- Potential sign-on bonus