Meet the TeamAs a Staff Machine Learning Engineer specializing in BEV (Bird's-Eye View) and Multi-Modal Perception, you will lead the development of next-generation models that unify information across cameras, LiDAR and radar to deliver a rich spatial understanding of the driving environment. You will drive architectural innovation, large-scale model training, and data-driven improvements that directly advance the perception capabilities at the heart of Torc's autonomous driving stack. This is a technical leadership role focused on model innovation and maturity, not downstream feature integration.
What You'll Do- 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.
What You'll Need to Succeed- 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.
Bonus Points- Experience with autonomous driving or robotics perception in production environments.
- Experience with MLOps and infrastructure tools (Ray).
- Hands-on expertise in BEV-based ML architectures, LiDAR-vision fusion, or spatial-temporal modeling.
- Familiarity with 3D labeling, calibration, and sensor simulation pipelines.
- Track record of publications or open-source contributions in top-tier venues (CVPR, ICCV, NeurIPS, ICRA, CoRL).
- Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy).
Work Location: For this position, we are open to hiring in Ann Arbor, MI in a hybrid capacity. We are also open to hiring Remote in the United States.
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
- 100% paid medical, dental, and vision premiums for full-time employees
- 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
- AD+D and Life Insurance
Job ID: 102945Hiring Range for Job Opening US Pay Range
$215,500-$258,600 USD
