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Applied AI Engineer, AI Hardware
Applied AI Engineer, AI HardwareTesla • Palo Alto, CA, United States
Applied AI Engineer, AI Hardware

Applied AI Engineer, AI Hardware

Tesla • Palo Alto, CA, United States
[job_card.variable_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

What To Expect

The AI Hardware Engineering team at Tesla is transforming EDA tools through AI-driven innovation to supercharge custom silicon for Full Self-Driving and Optimus robotics. We approach EDA as an end-to-end machine intelligence platform : infusing neural networks into synthesis, placement, routing, and verification flows, where every simulation cycle yields actionable data, every constraint optimization trains smarter algorithms, and every silicon revision hones our models for unprecedented speed and efficiency in next‑gen autonomous systems.

What You'll Do

  • Design and develop AI-powered applications ranging from static timing analysis to physical synthesis optimization and automation enhancements
  • Oversee the setup, configuration, and performance tuning of EDA tools for digital, analog, and mixed-signal design, including simulation (e.g., SPICE, Verilog simulators), synthesis, place‑and‑route, verification, and layout tools from vendors like Cadence, Synopsys, or Siemens
  • Create or customize solutions (e.g., in Tcl, Perl, or Python) to automate EDA flows, improve efficiency, and address specific design challenges in simulation, verification, or layout
  • Assist in formal verification, timing analysis, DRC / LVS checks, and ensuring designs meet fabrication standards
  • Collaborate cross‑functionally with software and hardware teams to accelerate the hardware development lifecycle
  • Strive to close the gap between AI-driven EDA and traditional sign-off ready tools

What You'll Bring

  • Degree in Electrical or Computer Engineering, Applied Physics, or related field, or equivalent experience with 3+ years developing and shipping production ML systems for hardware, EDA, semiconductor domains or equivalent
  • Strong VLSI foundation in analog / digital circuit design, including transistor-level modeling, layout parasitics, and custom IC flows
  • Expertise in Python + ML frameworks (PyTorch, TensorFlow, JAX); experience with graph ML (e.g., PyG, DGL) for netlists and geometric data
  • Hands‑on integration with EDA tools like Cadence Virtuoso, Spectre, Synopsys HSPICE, PrimeTime and familiarity with opportunities for AI enhancement
  • Knowledge of static timing analysis, routing tools, and potential AI applications
  • Proven track record in data pipelines for engineering datasets : curation, augmentation, and versioning for circuit simulation outputs
  • Bias for action, experimentation mindset, and ability to thrive in ambiguous, high-stakes environments with rapid prototyping
  • Benefits

  • 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
  • Expected Compensation

    $120,000 - $264,000 / 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.

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