The AI Test Systems Engineer at Tesla's AI Integration team focuses on developing scalable test platforms and automation systems to ensure the safety and reliability of Tesla's AI for self-driving vehicles and humanoid robotics. This role emphasizes building a feedback loop that drives AI evolution through simulation and real-world data integration. The engineer will work on creating backend services for test orchestration and data analysis, enabling rapid iteration and high reliability in AI systems. Overall, this position is critical in closing the loop between simulation and reality to foster real-world progress.

• Strong foundation in software engineering with a focus on system design, object-oriented programming, distributed systems, and scalable backend architectures.
• Advanced proficiency in Python, including object-oriented design, multi-threading, and scripting; experience with C++ is a plus.
• Deep hands-on experience building and owning HIL and/or SIL testing frameworks.
• Hands-on experience with containerization technologies such as Docker or Singularity and CI/CD tools like Jenkins, TeamCity, or Artifactory.
• Comfortable working in Linux/Unix environments with expertise in Bash, scripting, and low-level system debugging.
• Experience leveraging Agentic tooling in production systems.
• A relentless drive to improve quality without sacrificing velocity, with a proven ability to own end-to-end solutions from concept to deployment.
• Hands-on experience with simulation frameworks for autonomy or robotics.

• Develop innovative evaluation and test solutions across all of Tesla’s AI system features.
• Architect and implement next-generation test platforms that integrate Hardware-in-the-Loop (HIL), simulation, and AI-driven analysis.
• Design, build, and scale simulation environments and scenario-generation pipelines.
• Build scalable infrastructure-as-code solutions to automate CI/CD test workflows.
• Design systems that leverage AI/ML to identify edge cases and optimize test scenarios.
• Build scalable systems to aggregate, visualize, and extract actionable insights from test data.
• Collaborate closely with Autonomy and firmware teams to embed intelligent test frameworks into development pipelines.
• Integrate LLM-based tooling to automate root-cause analysis of test failures.

• 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.