Senior / Staff Software Engineer, ML-based Controls
About the role
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.
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The US yearly salary range for this role is: $241,000 - $320,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.
Responsibilities
- Design and develop data-driven and machine-learned approaches to vehicle control problems
- Develop learned models of vehicle behavior and dynamics
- Integrate models into closed-loop simulation
- Apply machine learning to improve controller adaptation
- Own problems end to end from conceptualization to validation
- Build data pipelines, evaluation metrics, and tooling
Qualifications
- MS/PhD or Bachelor's degree with a minimum of 4 years of industry experience
- Depth in control theory and dynamic systems
- Hands-on experience applying machine learning to physical systems
- Production-quality coding skill in Python and C++
- Experience with deep learning frameworks such as PyTorch
- Solid problem-solving skills using linear algebra, optimization, statistics & probability
Benefits
- Competitive perks & benefits
- Equity incentive awards
- Annual performance bonus
Skills mentioned
About Waabi
Waabi is pioneering Physical AI – starting with autonomous trucks. Press: press@waabi.ai Business: partnership@waabi.ai
H-1B sponsorship history
Historical employer filing data was found for Waabi. The employer record includes 27 historical certified applications. This is employer-level history, not a guarantee that this role currently offers sponsorship.