Senior ML Engineer – Localization & Sensor Fusion (Remote)

Torc Robotics

Michigan

Hybrid

USD 177,000 - 213,000

Full time

9 days ago

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Benefits offered by this job

Bonus and stock options

Health, dental, vision insurance

401K with 6% match

Flexible schedule

Paid vacation

Job summary

Torc Robotics is seeking a senior robotics software engineer to design, develop, and deploy production ML models for ego-motion estimation and localization across camera, LiDAR, and radar data. You will build scalable ML workflows, implement state estimation and sensor fusion, and analyze large vehicle datasets to drive improvements.

The role requires strong Python/C++ software skills and experience with PyTorch, SLAM/VO, and multi-sensor fusion.

Qualifications

Bachelor's degree in CS, Software Engineering, Robotics, or related field with 6+ years of experience.
Experience with AV or robotics localization (LiDAR, VO, SLAM, map-based pose).
Strong ML model development and deployment for perception/localization.
Proficiency with PyTorch and ML tooling for training, inference, and optimization.
Solid understanding of 3D geometry, probabilistic estimation, coordinate transforms, and robotics fundamentals.
Demonstrated ability to work with large multimodal datasets and build scalable pipelines.
Strong software engineering fundamentals in Python and C++, including algorithms, data structures, testing, debugging, and performance optimization.
Strong written and verbal communication skills and the ability to work effectively on cross-functional teams.

Responsibilities

Design, develop, and deploy production ML models for ego-motion estimation and localization, including learned pose estimation, sensor extrinsic calibration, map matching, and sensor fusion using camera, LiDAR, radar, and other vehicle sensors.
Develop scalable training and evaluation workflows using PyTorch, distributed training infrastructure, and large-scale real-world datasets.
Design and improve state estimation and sensor fusion algorithms for robust vehicle pose, velocity, and acceleration estimation.
Analyze large-scale vehicle data to characterize performance, identify failure modes, and drive model and system improvements.
Develop robust, efficient production software in modern C++ and Python across the full development lifecycle.
Define evaluation, verification, and validation strategies to ensure localization quality, robustness, and safety across diverse operating conditions.
Make technical design and architecture decisions, balancing model performance, computational efficiency, robustness, and production constraints.
Collaborate with perception, mapping, planning, controls, and platform teams to deliver integrated autonomous driving capabilities.
Provide technical leadership through design reviews, code reviews, mentoring, and development of engineering best practices.