Physics Informed Machine Learning Jobs in Santa Clara, CA

As Tesla continues to vertically integrate our operations, Tesla's in-house Cell Advanced Technology Engineering group is looking for a highly motivated Machine Learning Engineer. This is a critical role at the intersection of electrochemical science, manufacturing process control, and cutting-edge AI/ML development.

You will work closely with process development, equipment design, and data engineering teams to build intelligent models that drive deeper understanding of cell electrochemical reactions and unlock next-generation improvements in cell production quality, yield, and efficiency.

• Design, develop, and deploy end-to-end machine learning models and pipelines for cell manufacturing process optimization
• Build and maintain the design/process modeling frameworks, integrating data from multiple process stages into unified predictive and prescriptive models
• Collaborate with process engineers to identify high‑impact ML use cases across cell production steps
• Develop physics-informed machine learning models that incorporate electrochemical domain knowledge
• Work with large-scale manufacturing datasets using Python, SQL, and distributed computing frameworks
• Build and maintain data pipelines that interface with Tesla's Manufacturing Execution System (MES) and production databases
• Develop digital twin models to simulate process behavior and test control logic under various operating conditions
• Apply anomaly detection, time‑series forecasting, and reinforcement learning techniques to improve process stability and uptime
• Create intuitive dashboards and visualizations to communicate model outputs to engineering and operations stakeholders
• Establish model validation frameworks, monitor model performance in production, and drive continuous improvement

• Evidence of exceptional ability, including a strong understanding of ML fundamentals and demonstrated ability to apply them to real‑world, large‑scale engineering problems
• 5+ years of hands‑on experience in machine learning, data science, or a related field, preferably in a manufacturing or industrial setting
• Ph.D. in Chemical Engineering, Mechanical Engineering, Applied Mathematics, or equivalent experience
• Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit‑learn
• Experience with time‑series data modeling, anomaly detection, and predictive analytics
• Solid understanding of data engineering principles, including SQL, ETL pipelines, and working with production databases
• Familiarity with statistical modeling, experimental design, and model evaluation techniques
• Strong written and spoken English communication skills
• Ability to manage multiple projects simultaneously and work effectively under pressure in a fast‑paced environment

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

$91,600 - $195,600/annual salary + cash and stock awards + benefits

Pay 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.

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