Software Engineer, Frontier SI Infrastructure

Software EngineerWe are looking for strong software engineers to help scale the next generation of large AI models for Autopilot, Optimus & Digital Optimus. This role sits at the intersection of distributed systems, machine learning, and performance engineering. You will work closely with ML practitioners and infrastructure engineers to improve training efficiency, accelerate experimentation, and enable larger and more capable models.The ideal candidate is excited about both systems and machine learning.

You should be comfortable debugging distributed training issues, analyzing model behavior, and using data to demonstrate how infrastructure improvements translate into better model quality.You will help build and optimize large-scale training systems running on thousands of GPUs while developing the tools, metrics, and workflows needed to make model scaling faster and more predictable.ResponsibilitiesOptimize large-scale distributed training across thousands of GPUsImprove training throughput, utilization, reliability, and scalabilityDevelop tooling to identify bottlenecks in compute, networking, memory, and data pipelinesDesign and implement performance optimizations across PyTorch, CUDA, communication libraries, and training frameworksPartner with researchers to evaluate how infrastructure changes impact model quality, convergence, and downstream metricsAnalyze training runs and build dashboards that connect system performance to model outcomesDrive improvements in model scaling efficiency, including larger models, longer context lengths, and higher-quality datasetsDebug complex issues across software, hardware, networking, and machine learning systemsBuild infrastructure that accelerates experimentation and shortens iteration cycles for researchersRequirementsStrong software engineering fundamentals in Python and C++Experience with distributed systems, high-performance computing, or large-scale infrastructureUnderstanding of machine learning fundamentals, including optimization, training dynamics, and evaluationFamiliarity with PyTorch and modern deep learning frameworksAbility to analyze performance bottlenecks using profiling and observability toolsStrong debugging and problem-solving skillsExcellent communication and collaboration skillsCompensation & BenefitsBenefitsAlong 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 deductionFamily-building, fertility, adoption and surrogacy benefitsDental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contributionCompany 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 benefitsCompany paid Basic Life, AD&DShort-term and long-term disability insurance (90 day waiting period)Employee Assistance ProgramSick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid HolidaysBack-up childcare and parenting support resourcesVoluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insuranceWeight Loss and Tobacco Cessation ProgramsTesla Babies programCommuter benefitsEmployee discounts and perks programExpected Compensation $176,000 - $558,000/annual salary + cash and stock awards + benefitsPay 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.