Overview
On Site
Full Time
Skills
FOCUS
Generative Artificial Intelligence (AI)
Collaboration
Benchmarking
Performance Analysis
Optimization
Roadmaps
Computer Engineering
Electrical Engineering
Computer Science
Research
Artificial Intelligence
GPU
CPU
Parallel Computing
Python
C++
Modeling
Neural Network
Computer Hardware
Documentation
Presentations
Machine Learning (ML)
PPO
Payroll
Health Care
FSA
Finance
Apache Flex
Legal
Insurance
Job Details
Join Tesla's Self-Driving Hardware team to pioneer the next generation of AI accelerators and compute architectures for autonomous vehicles. In this role, you will focus on performance modeling, architectural exploration, and hardware-software co-design to optimize Tesla's custom machine learning silicon. The ideal candidate is an experienced Hardware Performance Engineer, with strong understanding of ML applications, and is comfortable working rapidly in a small-team environment.
Responsibilities
Requirements
Compensation and Benefits
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Responsibilities
- Develop performance models and simulation tools to evaluate hardware architectures for machine learning workloads
- Analyze and optimize neural network performance on current and next-gen AI accelerators
- Collaborate with hardware architects and software teams to identify bottlenecks, propose architectural improvements, and validate design trade-offs
- Create benchmarking frameworks to assess performance, power, and latency of ML workloads
- Conduct pre- and post-silicon performance analysis to correlate models with real-world hardware behavior
- Drive hardware-software co-optimization by translating neural network trends into architectural requirements
- Document and communicate findings to cross-functional teams to guide future hardware roadmaps
Requirements
- Engineering degree in Computer Engineering, Electrical Engineering, Computer Science, or related field or equivalent experience
- 3+ years of industry/research experience in performance modeling, hardware architecture, or ML acceleration
- Strong understanding of AI accelerators, GPU/CPU architectures, memory hierarchies, and parallel computing
- Proficiency in Python/C++ for modeling, analysis, and automation; familiarity with ML frameworks
- Knowledge of neural network architectures and their computational demands
- Proven ability to work with hardware/software teams to translate algorithmic needs into hardware features
- Clear documentation and presentation skills for technical and non-technical stakeholders
- Knowledge of compiler optimizations or ML graph lowering is a plus
Compensation and Benefits
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
- Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction
- Family-building, fertility, adoption and surrogacy benefits
- Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
- Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA
- Healthcare and Dependent Care Flexible Spending Accounts (FSA)
- 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
- Company paid Basic Life, AD&D, short-term and long-term disability insurance
- Employee Assistance Program
- Sick and Vacation time (Flex time for salary positions), and Paid Holidays
- Back-up childcare and parenting support resources
- Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
- Weight Loss and Tobacco Cessation Programs
- Tesla Babies program
- Commuter benefits
- Employee discounts and perks program
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.