Staff Machine Learning Engineer, Energy & Charging

Benefits

• Medical plans with multiple options and no employee premium deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental and vision coverage with no required employee contribution
• Company paid Health Savings Account (HSA) contribution when enrolled in a high-deductible plan with HSA
• Health Care and Dependent Care Flexible Spending Accounts (FSA)
• 401(k) with employer match, Employee Stock Purchase Plan, and additional financial benefits
• Company-paid Basic Life and AD&D insurance
• Short-term and long-term disability insurance (90 day waiting period)
• Employee Assistance Program
• Sick and vacation time, with flex time for salaried roles and accrued hours for hourly positions, plus paid holidays
• Back-up childcare and parenting support resources
• Voluntary benefits such as 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

What to Expect

This onsite role in Palo Alto, CA focuses on building predictive life models for charging and energy products. You will work with large-scale real-time datasets drawn from tests, manufacturing, and fleet operations to develop machine learning models that support prognostics and targeted design actions. Your work will influence products used by millions of Tesla customers.

Responsibilities

• Design, develop, train, and deploy predictive and control models of physical degradation, usage, and system performance
• Build robust, flexible, and automated software tools for complex real-time fleet analysis
• Design scalable and reliable data pipelines to productionize and monitor both new and existing models
• Translate complex business requirements and research findings into actionable insights and data-driven solutions
• Conduct research and stay current on AI/ML developments, with emphasis on physics-informed AI, to rapidly test and prototype new ideas

Requirements

• Production-quality Python code, experience with major deep learning frameworks, and software engineering best practices
• Practical C programming experience to integrate with firmware and bring ideas to shipped products
• Experience working with and optimizing large datasets, data pipelines, and AI models
• Strong foundation in linear algebra, probabilistic theory, numerical optimization, and deep learning, with hands-on implementation
• General knowledge of physics and engineering principles

Technologies

• Python
• C
• Major deep learning frameworks

Compensation

Expected compensation: USD 100,000 - 270,000 per year, plus cash and stock awards and benefits. Pay may vary based on location, knowledge, skills and experience. The total compensation may include additional elements; details of benefit plan participation will be shared if an offer is extended.