Staff, Machine Learning Engineer - BEV/Multi-Modal Perception
$216k - $259k • Remote, U.S, Ann Arbor, MI • Full-time
Posted 1mo ago
Job Location
Remote, U.S, Ann Arbor, MI
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
As 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.
Responsibilities
- Lead BEV model development, defining and executing the technical roadmap for BEV-based perception models.
- Design advanced multi-modal architectures that fuse heterogeneous sensor data into unified spatial representations.
- Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations.
- Own large-scale training workflows, including data sampling, augmentation, distributed training, and hyperparameter optimization.
- Advance model robustness and generalization for challenging conditions like low visibility and occlusions.
- Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.
- Collaborate with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.
- Mentor and guide ML engineers on best practices in experimentation, code quality, and model validation.
- Explore 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
- Competitive compensation package including bonus component and stock options
- 100% paid medical, dental, and vision premiums for full-time employees
- 401K plan with a 6% employer match
- Flexibility in schedule and generous paid vacation
- Company-wide holiday office closures
- AD+D and Life Insurance