Staff, ML Engineer - Road & Lane Detection
Torc Robotics14 days ago
Responsibilities
- Own the model roadmap for Road & Lane Detection from concept to production.
- Research, design, and train advanced neural architectures for road structure detection.
- Lead data strategy, defining curation and labeling policies.
- Develop metrics and evaluation frameworks for road geometry accuracy.
- Advance foundational capabilities like self-supervised pretraining.
- Drive large-scale experiments to identify scalable improvements.
- Collaborate with other teams to ensure model coherence.
- Mentor engineers and set best practices for model training.
Requirements
- 10+ years of experience in developing deep learning models for perception or computer vision.
- M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field.
- Deep expertise in semantic and instance segmentation, BEV modeling, or scene topology estimation.
- Strong understanding of lane and road geometry modeling and sensor projection.
- Proficiency with Python and modern ML frameworks like PyTorch.
- Experience with distributed training pipelines and large-scale dataset handling.
- Proven leadership in guiding technical roadmaps and mentoring engineers.
Benefits
- A competitive compensation package including a bonus component and stock options.
- Medical, dental, and vision coverage 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.