JobsAI Augmented Design Verification Engineer, AI Hardware
AI Augmented Design Verification Engineer, AI Hardware
TeslaAI Augmented Design Verification Engineer, AI Hardware
TeslaLocation
Palo Alto, CA
Type
Full-time
Posted
7/21/2026
Compensation
$128,000 - $312,000 a year
Undergraduate with 5+ Years of Experience
Approval 99.3%·Filings 1,102·New hires 320·
💎 Strong Sponsor
·FY 2025Job description
The Verification Engineer role at Tesla's AI Hardware team focuses on modernizing design verification flows by integrating AI/ML techniques into traditional UVM-based methodologies. The team is dedicated to developing advanced AI inference chips that enhance Tesla's machine learning capabilities. This position involves collaborating with multiple teams to create a flexible verification environment that improves efficiency and accelerates bug detection. The engineer will work at the intersection of silicon verification and applied AI, contributing to the development of tools that streamline the verification process.
Requirements
- 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
- Background contributing to or building internal AI-for-DV tooling
Responsibilities
- Develop and maintain UVM-based verification environments for digital IP and SoC subsystems
- Apply generative AI/LLM tools to auto-generate UVM sequences, assertions, testbench scaffolding, and verification plans from spec documents
- Apply AI/ML techniques to improve verification efficiency
- Use coverage-driven verification methodology to identify coverage holes and prioritize test generation
- Collaborate with design and DV automation teams to deploy ML models for bug triage and regression failure clustering
- Evaluate and integrate emerging AI-for-EDA tools into existing verification flows
- Maintain regression infrastructure and improve verification throughput and turnaround time
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.
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