Senior Machine Learning Engineer - Localization

Role overview

This senior engineering role sits on a team responsible for real-time estimation of vehicle pose, velocity, and acceleration for autonomous trucks. The work combines machine learning, probabilistic state estimation, and multi-sensor fusion to deliver safe and reliable localization under challenging real-world conditions. The position blends research-grade ML development with production software engineering for safety-critical automotive systems.

Responsibilities

- Design, train, and deploy ML models for ego-motion estimation, sensor extrinsic calibration, map matching, and multi-sensor fusion across camera, LiDAR, radar, and other vehicle inputs - Build scalable training and evaluation workflows using PyTorch and distributed infrastructure over large real-world driving datasets - Improve state estimation and sensor fusion algorithms for robust pose, velocity, and acceleration outputs under sensor degradation and environmental stress - Analyze fleet-scale vehicle data to characterize performance, identify failure modes, and drive systematic model and system improvements - Ship production-quality software in modern C++ and Python across the full development lifecycle, including verification and validation strategies for diverse operating conditions - Mentor peers, lead design and code reviews, and collaborate closely with perception, mapping, planning, controls, and platform teams on integrated driving capabilities

Requirements

- Bachelor's degree in computer science, software engineering, robotics, or related field with 6+ years of relevant industry experience, or Master's with 3+ years, or PhD with 1+ year - Hands-on experience with autonomous vehicle or robotics localization systems such as LiDAR-based localization, visual odometry, SLAM, or map-based pose estimation - Track record of developing and deploying ML models for perception, localization, or sensor fusion domains - Strong proficiency with PyTorch and modern ML tooling for training, inference, and optimization - Solid grounding in 3D geometry, probabilistic estimation, coordinate transforms, and core robotics fundamentals - Strong software engineering fundamentals in Python and C++, including algorithms, data structures, testing, debugging, and performance work

Nice to have

- Experience with state estimation methods such as factor graphs, Kalman filtering, or nonlinear optimization - Familiarity with distributed computing tools like Ray, Kubernetes, or similar orchestration frameworks - Knowledge of embedded and real-time constraints for on-vehicle deployment - Background in simulation, synthetic data generation, and uncertainty-aware ML modeling - Open-source contributions to robotics, perception, or ML frameworks - Familiarity with functional safety standards and automotive development processes, including ISO 26262

Benefits and work setup

- Competitive compensation package that includes a bonus component and stock options, with a published US hiring range of $177,300 to $212,800 USD - 100% employer-paid medical, dental, and vision premiums for full-time employees - 401(k) plan with a 6% employer match - Flexible scheduling and generous paid time off available from start date, plus company-wide holiday office closures - AD+D and life insurance coverage - Open to candidates based in Ann Arbor, Michigan on a hybrid schedule, or fully remote within the United States