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Staff, Machine Learning Engineer - BEV/Multi-Modal Perception at Torc Robotics · LumiJobs

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Torc Robotics· Posted 2026-09-04

Staff, Machine Learning Engineer - BEV/Multi-Modal Perception

Ann Arbor, MI full timeRemote

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senior

$216k–$259k

H1B: yes

Torc Robotics Staff Machine Learning Engineer at Torc Robotics leads development of BEV and multi-modal perception models for autonomous trucks. This role focuses on architectural innovation, large-scale model training, and improving perception capabilities.

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.

Qualification

Proven expertise in BEV modelingFamiliarity with 3D labelingWork Location

Required

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.

Preferred

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.

Benefits

Dental
Vision
401(k)
Equity/RSU
Life Insurance

Company

Torc Robotics

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Source: greenhouse

Active within the past hour

Remote-friendly

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Proven expertise in BEV modelingFamiliarity with 3D labelingWork Location

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