System Validation Engineer, AI Datacenter

What To Expect The Tesla AI Hardware team stands at the forefront of artificial intelligence innovation, developing custom silicon and compute infrastructure that redefine what’s possible in machine learning. Our team designs advanced AI accelerators and the datacenter systems that scale them—from Dojo, Tesla’s purpose‑built supercomputer, to the infrastructure that trains massive neural networks powering Full Self‑Driving (FSD) and Optimus, Tesla’s humanoid robot. Before any server, rack, or datacenter system goes into production, it must be rigorously validated to ensure it delivers the performance, reliability, and efficiency our AI workloads demand. What You’ll Do Design and implement automated validation frameworks for AI datacenter systems—servers, racks, networking, and storage—to ensure production readiness Develop and execute test suites to validate hardware functionality, performance benchmarks, thermal characteristics, and long‑term reliability under production AI workloads Build performance benchmarking and diagnostic tools to measure compute throughput, network bandwidth, storage I/O, power consumption, and thermal efficiency Automate data collection and analysis to track validation results, identify trends, and generate actionable insights for hardware design improvements Develop SW deployment, orchestration and testing pipelines with tools like Docker and configuration testing (e.g., Ansible) What You’ll Bring Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience 3+ years of experience in system validation, hardware testing, or test automation Proficiency in Python for test automation and data analysis Proven ability to design and implement automated test frameworks, including burn‑in testing, stress testing, and performance benchmarking Experience with datacenter systems validation and understanding of servers, networking equipment, storage systems, and power/thermal infrastructure Experience with distributed computing, containerization, orchestration, and CI/CD tools (e.g., SLURM, Docker, Kubernetes, Ansible) Strong debugging skills across hardware and software domains with ability to analyze complex data sets Preferred Qualifications Experience with AI/ML infrastructure or GPU cluster validation Background in statistical analysis, data visualization (Grafana, Kibana, Prometheus), or performance modeling Familiarity with Linux system administration, scripting (Bash, shell), and test frameworks (pytest, unittest) Experience utilizing lab test equipment and integrating it into automated hardware validation testing processes Knowledge of HPC technologies (Ethernet, InfiniBand, RDMA, PCIe, NVMe, or high‑speed interconnects) Benefits and Compensation Medical plans with $0 payroll deduction Family‑building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans with $0 paycheck contribution Company‑paid Health Savings Account (HSA) contribution when enrolled in the High‑Deductible 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&DD Short‑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 Backup childcare and parenting support resources Voluntary benefits including 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: $160,000 - $432,000 annual salary + cash and stock awards + benefits. #J-18808-Ljbffr Tesla