Sr. Controls, Modeling, and Simulation Engineer

About Rivian Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

Summary We are seeking a highly motivated Senior Controls Modeling and Simulation Engineer to join our Autonomy Controls team. The ideal candidate will have a strong background in motion planning, control systems, and vehicle dynamics, with experience in both modeling and simulation. You will play a key role in developing and improving advanced control algorithms and supporting a variety of projects critical to our next generation autonomous vehicle systems.

Design and implement high-performance control algorithms to solve real-time trajectory optimization and control problems. Design and implement optimization-based control strategies using convex and non-convex optimization techniques to solve control problems Collaborate with cross-functional teams to deliver improvements in vehicle motion planning, control, and feature engineering for L3/L4 autonomy. Optimize computational efficiency of control algorithms for real-time embedded implementation, including algorithm complexity reduction and solver selection. Support data analysis, KPI development, and embedded software integration for control features. Build and refine vehicle dynamics models to support simulation and validation of control strategies. Assist in the creation and maintenance of simulation environments for vehicle dynamics and control system validation. Contribute to the development and validation of new features through on-road and simulation-based testing.

Bachelor's or Master's degree in Mechanical Engineering, Electrical Engineering, Robotics, Computer Science, or a related field. Strong background in motion planning, control theory, and vehicle dynamics. 3+ years of experience in optimization theory and its application to control systems design and proficiency with optimization solvers and frameworks. Proficiency in programming languages such as C++ and Python. Knowledge of optimization algorithms including gradient descent, interior point methods, and sequential convex programming. Familiarity with multi-objective optimization and trade-off analysis for competing control objectives (comfort, safety, efficiency). Strong background in machine learning, AI, and robotics, with hands-on experience developing and deploying learning-based algorithms. Experience with embedded systems and real-time control implementation is a plus. Excellent problem-solving skills and ability to work collaboratively in a fast-paced environment. Prior internship or project Pay Disclosure The salary range for this role is $179,000.00 - $223,800.00 for California based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs. The successful candidate may be eligible for annual performance bonus and equity awards. We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may