Vehicle Dynamics Modeling Engineer, Simulation Infrastructure

What To Expect:

As a Vehicle Dynamics Simulation & Data Analysis Engineer at Tesla, you will be at the forefront of developing the tools that define the performance of our next-generation vehicles. This role is a unique opportunity to merge your passion for vehicle dynamics, software development, and data science to directly impact products that accelerate the world's transition to sustainable energy.

You will be a key contributor to our advanced simulation toolchain, working from first principles to model complex vehicle behaviors. Your expertise will be crucial in transforming vast amounts of simulation and real-world test data into actionable insights that drive engineering decisions. This position requires a meticulous, data-driven engineer who thrives in a fast-paced, collaborative environment and is committed to solving the most challenging problems in vehicle performance.

What You'll Do:

Architect, develop, and maintain a world-class vehicle simulation toolchain for both offline analysis and driver-in-the-loop (DIL) simulator applications Develop and maintain robust data pipelines to process, analyze, and visualize terabytes of data from simulations, track testing, and our global vehicle fleet Apply statistical analysis and machine learning techniques to correlate simulation models with real-world performance data, identifying key performance indicators and areas for improvement Create intuitive data visualization dashboards and tools to provide actionable insights to vehicle dynamics, controls, and hardware engineering teams Collaborate closely with vehicle development engineers to define requirements, develop new model features, and ensure simulation accuracy Troubleshoot complex issues within the simulation ecosystem and lead data-driven correlation efforts to enhance predictive accuracy

What You'll Bring:

Degree in Mechanical Engineering, Computer Science, or related field, or equivalent experience Minimum of 2 years of experience in motorsport, automotive, or software development environments Strong proficiency in Python for data analysis with libraries like Pandas, Num Py, and Sci Py, and familiarity with at least one systems programming language such as C++, Rust, or CProven experience analyzing large datasets to derive engineering insights Solid understanding of vehicle dynamics principles and practical experience with vehicle hardware and suspension components Demonstrated work ethic, integrity, and ability to manage multiple priorities in a dynamic environment

, Tesla