Machine Learning Modeling Engineer , Cell Manufacturing

What to Expect

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.

What You’ll Do

• 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

What You’ll Bring

• E vidence 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 Tensor Flow, Py Torch, 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