Staff Machine Learning Engineer on Merchant team at Pinterest. Leading ML initiatives to enhance merchant quality and improve user shopping experiences.
About the role
- Staff Engineer in machine learning at Torc Robotics developing next-gen perception models. Leading architectural innovations and large-scale model training for autonomous vehicle technology.
Responsibilities
- Lead the development of the BEV model: define and execute the technical roadmap for BEV-based perception models across multiple tasks (e.g., detection, segmentation, road topology, and scene understanding).
- Design advanced multimodal architectures that fuse heterogeneous sensor data (camera, LiDAR, radar, HD maps) into unified spatial representations.
- Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations.
- Own large-scale training workflows, from data sampling strategies and augmentation pipelines to distributed training and hyperparameter optimization.
- Improve model robustness and generalization, accounting for long-tail conditions such as low visibility, occlusions, and rare scene configurations.
- Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.
- Collaborate cross-functionally with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.
- Mentor and guide machine learning engineers, cultivating best practices in experimentation, code quality, and model validation.
- Remain at the forefront of machine learning research, exploring self-supervised learning, large-scale pretraining, and foundation models for 3D perception.
Requirements
- Master’s degree or PhD in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent practical experience).
- 10+ years of experience in deep learning for perception, 3D vision, or autonomous systems.
- Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
- Strong experience in multimodal sensor fusion, particularly integrating camera and LiDAR data.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Experience with large-scale data pipelines, distributed training, and experiment/experiment-management systems.
- Demonstrated leadership in driving ML model innovation and mentoring technical teams.
Benefits
- Competitive compensation program including bonus components and stock option grants
- Medical, dental, and vision coverage for full-time employees
- Retirement savings plan (RRSP) with a 4% employer contribution
- Public transit subsidy (Montreal region only)
- Flexible work hours and generous paid time off
- Company-wide office closures during major holidays
- Life insurance
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