Post Silicon Validation Engineer, SI Hardware
teslaPalo Alto (CA)
$128,000 - $354,000/annual
Apply (opens in a new tab)Post Silicon Validation Engineer, SI Hardware
Posted today
teslaPalo Alto (CA)
SENIORITY
Lead
SALARY
$128,000 - $354,000/annual
About the role
Tesla Si Hardware TeamThe Tesla SI 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 SI inference chips tailored to accelerate Tesla's machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet. The work of Tesla's SI 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 SI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life. The role will focus on developing post-silicon validation plans, tools, and infrastructure for Tesla's custom SoCs and platform designs. As a Post-Silicon Validation Engineer, the candidate will take on challenges like validating the neural-network inference and vision compute pipeline, performing system level power characterization, and troubleshooting complex hardware bugs and field returns. The candidate will regularly take part in hardware design and schematics review, firmware development, and building automated test infrastructures for running large volume of post-silicon system level tests. The role also extends into pre-silicon validation on hardware emulation platforms and into developing production test content for system level test (SLT).
Responsibilities:
- Create and execute synthetic workloads that stress the various functional blocks inside the silicon platforms, such as the inference compute pipeline, vision/camera interface, fabric, and memory subsystem
- Analyze how machine learning workloads execute on the inference compute pipeline, identifying bottlenecks and gaps to improve test coverage
- Bring up and characterize Autopilot Custom Silicon and PCBA, with a focus on the neural-network inference compute pipeline
- Develop and run validation content on hardware emulation platforms ahead of tapeout
- Review RTL and microarchitecture with the design team, raising issues and feedback before tapeout
- Collaborate with diverse teams — hardware design, system/microarchitecture, ML model design, compiler engineering, and firmware — on schematic reviews, co-design decisions, and automated test infrastructure
- Write test plans, develop test cases, and catch design bugs before production, assisting in root-causing and fixing issues as they're found
- Contribute to code reviews for test infrastructure and automation to maintain code quality and reliability
- Develop production test content for system level test (SLT), partnering with SLT and ATE engineers
- Characterize and improve power and performance consumption at a system level
Requirements:
- Degree in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience
- Deep knowledge of computer architecture
- Ability to read RTL (Verilog/SystemVerilog) well enough to review designs and raise issues
- Microcontroller & Embedded Systems Programming Experience in C/C++Python and bash scripting
- Familiarity with git and version control systems
- Design, verification or validation disciplines, system/platform level debug and root cause isolation, methodology and tools
- Experience with Test Automation Framework Development
- Familiarity with neural network / ML inference concepts — including LLM and transformer architectures, training, and inference optimization — and awareness of broader trends in ML workloads and simulation methodologies, useful for keeping test coverage relevant as silicon and workloads evolve
Compensation & 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 HSAHealthcare 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&DShort-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
- Weight Loss and Tobacco Cessation Programs
- Tesla Babies program
- Commuter benefits
- Employee discounts and perks program
- Earned Wage Access: Real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr. Managers levels)
- Expected Compensation $128,000 - $354,000/annual salary + cash and stock awards + benefits
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.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.