The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence through cutting-edge hardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla's machine learning capabilities. The work of Tesla s AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Tesla remains a leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life.
The AI Hardware team is looking for a Verification Engineer to help modernize our design verification flows by integrating AI/ML-driven techniques into traditional UVM-based methodologies. You'll work at the intersection of silicon verification and applied AI - building tools that accelerate coverage closure, automate testbench/stimulus generation, and surface bugs faster than conventional constrained-random approaches alone. You will interact with multiple teams and build a metric-driven, configurable, and flexible verification environment.
We are open to hiring in Palo Alto, CA and at all levels.
Develop and maintain UVM-based verification environments for digital IP and SoC subsystems
Apply generative AI/LLM tools (e.g., Claude) to auto-generate UVM sequences, assertions, testbench scaffolding, and verification plans from spec documents - with appropriate review for correctness and coverage gaps
Apply AI/ML techniques (e.g., LLM-assisted test generation, ML-based coverage prediction, anomaly detection in waveform/log data) to improve verification efficiency
Use coverage-driven verification (CDV) methodology, identifying coverage holes and prioritizing test generation using data-driven/ML-assisted analysis
Collaborate with design and DV automation teams to deploy ML models for bug triage, regression failure clustering, and root-cause analysis
Evaluate and integrate emerging AI-for-EDA tools into existing verification flows
Maintain regression infrastructure and improve verification throughput/turnaround time
Degree in Electrical Engineering, Computer Engineering, or related field, or equivalent experience
5+ years of experience in ASIC/SoC functional verification using UVM/SystemVerilog
Strong understanding of coverage-driven verification methodology
Experience with verification IP (VIP) integration and protocol verification (e.g., APB, AXI, SPI, I2C)
Familiarity with scripting (Python preferred) for automation and tooling
Exposure to or strong interest in applying ML/AI techniques to EDA/verification problems
Hands-on experience using LLM-based coding assistants (e.g., Claude) for RTL/UVM code generation, debug assistance, or documentation, including effective prompt engineering for hardware-specific tasks
Background contributing to or building internal AI-for-DV tooling
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Medical plans > 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 Accounts) HSA Contribution when enrolled in the High-Deductible 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 (90 day waiting period)
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly 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
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.