Senior Machine Learning Engineer – Road & Lane Detection

Torc Robotics • Montreal • 2w ago

Meet the Team

At Torc Robotics, we're on a mission to revolutionize freight movement through safe, efficient, and reliable autonomous driving technology. Backed by Daimler Truck, we are industry leaders in Level 4 autonomous vehicle systems, with decades of innovation and a clear path to commercialization. Join our growing Model Development team and directly contribute to our world-class machine learning systems for Road & Lane detection– a critical function in enabling AV perception and path planning.

We are seeking a highly motivated Senior Machine Learning Engineer to join our Road & Lane Detection team focused on developing robust models that predict static and semi-static road features (lanes, intersections, boundaries, driveable space, etc). You will be responsible for designing and implementing state-of-the-art deep learning models that enable our autonomous vehicles to understand and anticipate road structures in diverse environments.

This is a hands-on applied research and development role, with direct impact on Torc’s core autonomy stack.

What You’ll Do

Design, train, and deploy deep learning models for road and lane topology prediction, including drivable space, lane boundaries, and intersection structures.
Build and optimize neural network architectures that leverage multi-modal sensor data (camera, LiDAR, radar) and SD/HD map context.
Collaborate with teams across perception, mapping, planning, and systems integration to ensure seamless performance in real-world autonomous driving.
Lead model ablation studies, error analysis, and performance validation using large-scale simulation and real-world datasets.
Develop tooling and workflows to automate training, experimentation, and evaluation of ML models.
Mentor junior engineers and contribute to technical leadership within the ML modeling group.

What You’ll Need to Succeed

Bachelor's degree in computer science, data science, artificial intelligence or related field with 6+ years of professional experience or a master's degree with 4+ years of experience
Hands on experience with segmentation tasks like lane prediction, free space segmentation, etc.
State of the Art AV experience with multi-sensor data, especially in perception systems for autonomous vehicles or robotics.
Mastery of Python and PyTorch, with the ability to transition research level code to production and deployment ready standards
Proficiency in Python, and familiarity with modern ML Ops tools and GPU-based training.
Prior experience in autonomous driving, robotics, or similar safety-critical domains.
Experience with LiDAR, radar, or 3D spatial data processing.
Knowledge of performance metrics for perception and prediction tasks (IoU, FDE, ADE, mAP).

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.

Bonus Points

PhD in machine learning or data science
Proficient in writing CUDA kernels and developing custom PyTorch operations.
Experience with relevant NVIDIA libraries and frameworks, such as CUBLAS, CuDNN, and NPP
Proficiency with Ray
Publications or contributions to open-source ML projects.
C++ skills or experience integrating ML into production autonomy systems.

Perks of Being a Full-time Torc’r

Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:

A competitive compensation package that includes a bonus component and stock options
Medical, dental, and vision for full-time employees
RRSP plan with a 4% employer match
Public Transit Subsidy (Montreal area only)
Flexibility in schedule and generous paid vacation
Company-wide holiday office closures
Life Insurance

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.

Job ID: R-102375