Senior Machine Learning Engineer - Localization (Autonomous Vehicles)

Location: Remote in the United States, or hybrid in Ann Arbor, Michigan

Salary: $177,300–$212,800 USD annually, plus bonus and stock options.

Company

Develops production software and autonomous driving solutions for automated trucks, with a focus on commercializing autonomous vehicle technology.

What you will do

• Design, develop, and deploy production machine learning models for ego-motion estimation and localization, including pose estimation, sensor calibration, map matching, and sensor fusion.
• Build scalable PyTorch training and evaluation workflows using distributed infrastructure and large-scale real-world datasets.
• Improve state estimation and sensor fusion algorithms for vehicle pose, velocity, and acceleration estimation.
• Analyze vehicle data, identify failure modes, and define validation strategies for localization quality, robustness, and safety.
• Develop production software in modern C++ and Python while making architecture decisions under computational and real-time constraints.
• Collaborate with perception, mapping, planning, controls, and platform teams, and provide technical leadership through design reviews, code reviews, and mentoring.

Requirements

• Bachelor’s degree with 6+ years of relevant industry experience, Master’s degree with 3+ years, or PhD with 1+ year.
• Experience with autonomous vehicle or robotics localization systems, such as LiDAR localization, visual odometry, SLAM, or map-based pose estimation.
• Experience developing and deploying machine learning models for perception, localization, or sensor fusion, with proficiency in PyTorch and modern ML tooling.
• Strong understanding of 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals.
• Experience with large multimodal datasets and scalable processing, labeling, and evaluation pipelines.
• Strong Python and C++ software engineering skills, including algorithms, testing, debugging, and performance optimization.

Nice to have

• Experience with factor graphs, Kalman filtering, nonlinear optimization, or related state estimation methods.
• Familiarity with Ray, Kubernetes, or similar distributed computing and orchestration tools.
• Knowledge of embedded and real-time on-vehicle constraints, simulation, synthetic data, or uncertainty-aware ML.
• Experience with open-source robotics, perception, or ML frameworks and functional safety standards such as ISO 26262.

Culture & Benefits

• Collaborative, energetic, and team-focused work environment.
• Competitive compensation with bonus and stock options.
• 100% employer-paid medical, dental, and vision premiums for full-time employees.
• 401(k) plan with a 6% employer match, life insurance, and AD&D insurance.
• Flexible scheduling, generous paid vacation available immediately after starting, and company-wide holiday office closures.