JobsStaff SoC Product & Test Engineer, AI Hardware
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Staff SoC Product & Test Engineer, AI Hardware

Tesla

Location

Palo Alto, CA

Type

Full-time

Posted

4/22/2026

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 2025

Job description

Tesla's AI Hardware team is seeking a highly motivated ASIC RTL Design Engineer to design high-performance, power-efficient RTL for AI training and inference systems. The role focuses on tensor operations, matrix computations, and optimized data paths, contributing to the development of advanced AI accelerators.

Requirements

  • Degree in Electrical Engineering, Computer Engineering, or related field, or equivalent experience
  • 10+ years across SoC characterization, yield, diagnostics, and IP test engineering
  • Hands-on experience across ATE, SLT, and bench platforms
  • Deep expertise in PVT characterization, guard band definition, and ATE/SLT correlation
  • Experience with diagnostic data pipelines and AI/ML-based fault isolation techniques
  • IP test development experience for High-Speed IO and Mixed Signal IPs
  • Ability to use agentic AI flows to automate yield analysis, diagnostics, and test optimization

Responsibilities

  • Define characterization plans for processor cores and IPs — develop NPI performance stress tests across process, voltage, and temperature
  • Perform and correlate measurements across ATE and SLT platforms over volume — define guard bands and drive corrective actions for test platform alignment
  • Develop solutions to set optimal system voltage and frequency operating points — align from manufacturing screen through system operation
  • Own silicon bring-up — execute structural, functional, and parametric tests; debug failures and quantify performance shifts using accelerated stress
  • Analyze volume production data — identify and implement solutions to improve yield and throughput
  • Architect and deploy volume diagnostic data processing pipelines for SoC logic and memory
  • Integrate AI-based deep learning techniques to improve diagnostics convergence, fault isolation, and failure analysis success rates
  • Drive defect reduction with foundry partners — build defect paretos, recommend FA candidates, and validate improvements from process changes
  • Develop models to predict yield trends, detect anomalies, and drive corrective actions
  • Root cause qualification fails and field returns — develop new test content targeting identified fault types

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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