AI Hardware Performance Engineer

Job Description

Join Tesla to contribute to the implementation of hardware systems that enable advanced AI for vision and planning, supporting Tesla's vision of deploying autonomy at scale in vehicles and robots.

Requirements

• Degree in Computer Science, Computer Engineering, or Electrical Engineering
• Good understanding of GPU architecture and AI accelerators
• Proficiency in computer architecture
• Proficiency in at least one programming language such as C, C++, Python
• Experience with writing performance tests and analyzing results
• Experience with debugging performance bottlenecks and issues
• Experience with architectural simulators is a plus
• Previous internship and/or project experience is a plus
• Ability to root cause performance issues and debug esoteric symptoms
• Professional and positive communication skills

Responsibilities

• Analyzing and deploying state-of-the-art neural networks on GPU, AI accelerator, and performance models
• Debugging performance bottlenecks and issues in hardware or simulation
• Conducting pre- and post-silicon performance analysis to correlate models with real-world hardware behavior
• Proposing new hardware features, backed by performance estimates
• Creating benchmarking frameworks to assess performance, power, and latency of ML workloads
• Documenting and communicating findings to cross-functional teams to guide future hardware roadmaps
• Developing performance models and simulation tools to evaluate hardware architectures for machine learning workloads

Benefits

• Employees at Tesla are often offered day-one coverage with multiple medical options (some at $0 paycheck cost), dental/vision, company HSA contributions, a 401(k) match, and equity programs. Most roles also include paid time off and holidays, family-building support, employee assistance, commuter and childcare benefits, and access to discounts and wellness programs.