Machine Learning Engineer, Energy Hardware Engineering

paid holidays, flex time, 401(k) United States, California, Palo Alto Jul 13, 2026 What to Expect

The Tesla Energy Products Field Quality team is looking for a passionate and collaborative Machine Learning Engineer to bridge large-scale fleet data to system-based modeling & analytical efforts across the Tesla Energy portfolio: Industrial, Residential, Supercharger, and Solar.

You will work across the systems engineering ecosystem - building the shared data and AI/ML foundations that system teams depend on. Where our first-principles models tell us how a system should behave, you will help quantify how the fleetactually behaves, and turn that signal into better models, faster investigations, and earlier detection of issues in the field. You will helpestablisha unified fleet data layer and a consistent ML standard that systems teams can build on. What You’ll Do

• Develop ML and statistical methods that improve how we understand fleet behavior - from augmenting first-principles system models to detecting anomalies and emerging failure trends across energy products

• Help build a unified fleet data layer and ingestion foundation that systemteams canconsume

• Model the gap between expected andobservedfleet behavior and turn it into actionablesignalfor systems teams

• Quantify uncertainty so teams across the ecosystem can reasonaboutrisk with statistical rigor

• Establish a consistent AI/ML and data standard - training, evaluation, validation, and tooling - applied cohesively across systems engineering teams

• Partner across disciplines so knowledge, methods, and integrations evolve through multi-disciplinary feedback and a shared source of fleet truth

• Strong quantitative foundation - physics, applied math, or a related engineering discipline - with the ability toreason aboutphysical systems from first principles

• Strong ML fundamentals: model development, training, evaluation, and a real understanding of when and why models work

• Experience with physics-informed or scientific ML (e.g., physics-informed neural networks, surrogate/data-driven modeling, differentiable simulation, system identification) - or a clear aptitude and excitement to work there

• Strong Python in a scientific/ML setting (NumPy, pandas,PyTorch/JAX or similar; visualization tools as needed)

• Experience withuncertainty quantification, probabilistic modeling&time-series analysis

• Comfort working with large-scale data and the pipelines/tooling needed to make it model-ready (SQL, Spark, and similar)

• Software fundamentals: version control (Git), and familiarity with CI/CD and containerization (Docker, Kubernetes)

• A collaborative, first-principles mindset,and the drive to tackle fundamental, open-ended problems

Along 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 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 Accounts) 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&D
• 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
• 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 $124,000 - $258,000/annual salary + cash and stock awards + benefits