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Senior / Staff Software Engineer, ML-based Controls

Waabi

Remote · CAFull-time$241–320K/yrPosted 2w agoStill listed 6 days ago

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At a glance

Compensation
$241–320K/yr
Location
Remote · CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

The role designs and develops data‑driven machine‑learned vehicle control solutions, builds models and integrates them into simulations, and creates pipelines and metrics to evaluate performance, while collaborating with multidisciplinary engineers and researchers to advance safe self‑driving technology.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningRoboticsDynamical SystemsOptimal ControlSystem IdentificationDeep LearningLinear AlgebraStatisticsProbabilityPrototypingCollaborationProblem SolvingControlsMechanical EngineeringElectrical EngineeringComputer ScienceControl TheoryDynamic SystemsMPCState EstimationKinematic Vehicle ModelingDynamic Vehicle ModelingPythonC++PyTorchOptimization

Qualifications

MS/PhD or Bachelors DegreeMinimum 4 Years Industry Experience

Full job description

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.

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.

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