Staff ML Engineer — Road & Lane Perception

Torc Robotics; Mount Royal; Hybrid; CAD 209,000 - 314,000; Full time

Job summary

A leading autonomous vehicle technology company in Montreal seeks a Staff Machine Learning Engineer for Road & Lane Detection. This role involves leading model development to enhance perception of road geometry and lane structures using advanced deep learning techniques. The ideal candidate has over a decade of experience in computer vision and deep learning, with expertise in model innovation and mentorship of fellow engineers. The position offers competitive compensation and a hybrid work model.

Benefits

Competitive compensation package including bonus 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

Qualifications

• 10+ years of experience developing deep learning models for perception or computer vision at scale.
• Strong understanding of lane and road geometry modeling, camera calibration, and sensor projection.
• Experience with distributed training pipelines and large-scale dataset handling.

Responsibilities

• Own the model roadmap for Road & Lane Detection within the Model Dev ML org.
• Research, design, and train advanced neural architectures.
• Lead data strategy for this domain — defining data curation and labeling policies.

Skills

Deep learning models for perception

Computer vision

Python proficiency

Distributed training pipelines

Education

M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field

Tools

PyTorch

Job description

A leading autonomous vehicle technology company in Montreal seeks a Staff Machine Learning Engineer for Road & Lane Detection. This role involves leading model development to enhance perception of road geometry and lane structures using advanced deep learning techniques. The ideal candidate has over a decade of experience in computer vision and deep learning, with expertise in model innovation and mentorship of fellow engineers. The position offers competitive compensation and a hybrid work model.