Senior / Staff Machine Learning Engineer, Vehicle Dynamics
Required skills
- ML-based Controls
- data-driven
- machine-learned
- vehicle control
- vehicle behavior
- vehicle dynamics
- closed-loop simulation
- AI-first approach
- self-driving
- offline experimentation
Nice to have
- MS/PhD
- physical system
- production-quality coding
- deep learning frameworks
- rapidly prototype
- test new algorithms
Role summary
Seeking a Senior/Staff Software Engineer specializing in ML-based Controls for self-driving vehicles. This role involves designing and developing data-driven and machine-learned approaches to vehicle control, integrating learned models of vehicle behavior, and applying ML to improve controller adaptation. You will work within an AI-first team, owning problems from conceptualization to validation, and building necessary data pipelines and tooling. The position requires strong coding skills in Python and C++, experience with deep learning frameworks like PyTorch, and demonstrated depth in control theory and dynamic systems. A minimum of 4 years of industry experience in a relevant technical field is required.
You Will…
-
Design and develop data-driven and machine-learned approaches to vehicle control problems, bringing modern ML to a domain traditionally solved with classical methods.
-
Develop learned models of vehicle behavior and dynamics, and integrate them into the closed-loop simulation.
-
Apply machine learning to improve how the controller adapts across vehicles and operating conditions.
-
Be part of a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale.
-
Own problems end to end, from conceptualization and offline experimentation through simulation and on-vehicle validation.
-
Build the data pipelines, evaluation metrics, and tooling needed to measure whether a learned approach outperforms the classical baseline.
-
Participate and share ideas in technical and architecture discussions, helping define how learning and classical control coexist in a safety-critical stack.
Qualifications:
-
MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Robotics, Controls, Mechanical/Electrical Engineering, Computer Science and/or similar technical field(s) of study.
-
Demonstrated depth in control theory and dynamic systems (e.g., MPC, optimal control, state estimation, system identification, kinematic and dynamic vehicle modeling).
-
Hands-on experience applying machine learning to a physical system, with real hardware in the loop rather than simulation alone.
-
Production-quality coding skill in Python and C++, and experience with deep learning frameworks such as PyTorch.
-
Solid problem solving skills using linear algebra, optimization, statistics & probability.
-
Ability to rapidly prototype and test new algorithms, and to design the experiments that prove whether they work.
-
Open-minded and collaborative team player with the willingness to help others.
-
Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
Similar roles
- Senior / Staff Safety & Systems Technical Program ManagerWaabi · Remote · Remote
- Creative DirectorWaabi · San Francisco, CA · Hybrid
- Staff Software Engineer, SalesforceDAT Freight & Analytics · Denver, CO · Hybrid
- Senior Software Engineer (Remote)Weedmaps · Remote · Remote
- Software Engineer II - Seller ExperienceStubHub · New York, NY · Hybrid
- Senior Software Engineer, Cloud ApplicationsTemporal · Remote · Hybrid
