Director of MLOps at Manulife leading AI deployments and scalable solutions in Canada. Architecting MLOps capabilities to ensure governance and reusable AI solutions across segments.
About the role
- Staff ML Engineer specializing in BEV and Multi-Modal Perception at Torc Robotics. Leading development of next-gen models for rich spatial understanding in autonomous trucks.
Responsibilities
- Lead BEV model development: 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 multi-modal 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.
- Advance model robustness and generalization, addressing 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 ML engineers, cultivating best practices in experimentation, code quality, and model validation.
- Stay at the forefront of ML research, exploring self-supervised learning, large-scale pretraining, or foundation models for 3D perception.
Requirements
- 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems
- M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience).
- Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
- Strong background in multi-modal 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 management systems.
- Demonstrated leadership in driving ML model innovation and mentoring technical teams.
Benefits
- 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
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