Senior, ML Engineer - Learned Localization

Location: Montreal

Senior, ML Engineer - Learned Localization
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About The Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.

Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Meet the Team
As a Senior ML Engineer focused on Localization & Perception, you’ll build the machine-learning component that enables Torc’s autonomous trucks to understand precisely where they are in the world. We work across sensor fusion, map-based localization, and learning-based pose estimation to deliver robust, real-time localization in challenging environments. As part of a multidisciplinary group of ML engineers and researchers in Autonomy, you’ll collaborate closely across ML teams to build production-grade solutions that advance Torc’s mission of safe, reliable autonomous trucking.

What You’ll Do

Design, build, and optimize ML models for localization, including learned pose estimation, map-matching, and sensor fusion pipelines using camera, LiDAR, and radar data.

Develop high-performance training and evaluation workflows, leveraging frameworks such as PyTorch, distributed training infrastructure, and large-scale datasets.

Collaborate with robotics and mapping engineers to integrate localization models into the autonomy stack, ensuring performance, stability, and real-time constraints are met.

Analyze failure cases, run ablations, improve model robustness, and drive rigorous experimentation to achieve production-level reliability.

Contribute to system design, code reviews, best practices, and documentation across the ML and autonomy organization.

What You’ll Need To Succeed

Bachelor’s degree in Computer Science, Software Engineering, or related field with 6+ years of professional applied MLE engineering experience in Autonomous Vehicle, Robotics or related industry.

Master’s degree in Computer Science, Software Engineering, or related field with 3+ years of professional applied MLE engineering experience in Autonomous Vehicle, Robotics or related industry.

Experience with AV or robotics localization systems (e.g., LiDAR-based localization, visual odometry, SLAM, or map-based pose estimation).

Strong experience developing and deploying ML models in perception, localization, or sensor fusion domains.

Proficiency with PyTorch and modern ML tooling for training, inference, and optimization.

Solid understanding of 3D geometry, probabilistic estimation, spatial transforms, and robotics fundamentals.

Demonstrated ability to work with large multimodal datasets and build scalable pipelines for processing, labeling, and evaluation.

Strong software engineering skills in Python or C++, with a focus on clean, maintainable, production-ready code.

Excellent communication skills and the ability to collaborate in a fast-paced, cross-functional environment.

Bonus Points!

Familiarity with distributed computing tools such as Ray, Kubernetes, or similar orchestration frameworks.

Knowledge of embedded and real-time constraints for on-vehicle deployment.

Experience in simulation, synthetic data generation, and uncertainty-aware ML modeling.

Contributions to open-source robotics, perception, or ML frameworks.

Knowledge of English is required since the selected candidate will need to collaborate daily with English-speaking colleagues in the United States and work with technical documentation written exclusively in English.

Work Location
For this position, we are open to hiring in either the Torc Montreal, Quebec (Canada) or Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States or Canada.

Perks of Being a Full-time Torc’r…