Torc Robotics · 3 days ago
Staff, ML Engineer - Road & Lane Detection
Ann Arbor, MI
Full-time
Hybrid
Lead/Staff
$220K/yr - $330K/yr
10+ years expTorc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. As a Staff Machine Learning Engineer, you will lead the model development for Road & Lane Detection, defining deep learning architectures and data-driven approaches to enhance the perception capabilities of autonomous vehicles.
Autonomous VehiclesRoboticsSoftware
Responsibilities
Own the model roadmap for Road & Lane Detection within the Model Dev ML org — from concept through production-grade model maturity
Research, design, and train advanced neural architectures (e.g., multi-camera BEV transformers, LiDAR-vision fusion models, topological lane graph networks) to detect, segment, and model road structures and lane connectivity
Lead data strategy for this domain — defining data curation, labeling policies, and active learning pipelines to capture long-tail scenarios (e.g., occlusions, complex merges, construction zones)
Develop robust metrics and evaluation frameworks for lane and road geometry accuracy, temporal consistency, and cross-domain generalization
Advance foundational capabilities such as self-supervised pretraining, synthetic-to-real adaptation, and temporal modeling for road and lane understanding
Drive large-scale experiments — designing, running, and analyzing results from distributed training workflows and ablations to identify scalable improvements
Collaborate with other model dev/perception teams to ensure model coherence and interface consistency
Mentor engineers and scientists, setting best practices for model training, evaluation, and code quality
Stay ahead of the research frontier by evaluating and adapting emerging techniques (e.g., BEV-based large models, vectorized map prediction, lane graph transformers) to production-grade perception
Qualification
Required
10+ years of experience developing deep learning models for perception or computer vision at scale
M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or equivalent experience)
Deep expertise in semantic and instance segmentation, BEV modeling, or scene topology estimation
Strong understanding of lane and road geometry modeling, camera calibration, and sensor projection
Proficiency with Python and modern ML frameworks (e.g., PyTorch, Lightning)
Experience with distributed training pipelines, experiment management, and large-scale dataset handling
Proven leadership in guiding technical roadmaps, mentoring engineers, and driving measurable model improvements
Preferred
Experience developing ML models for autonomous driving, mapping, or ADAS systems
Familiarity with multi-modal fusion (camera, LiDAR, radar, HD maps)
Hands-on experience with BEV-based and topological prediction models
Contributions to perception-related ML research (CVPR, NeurIPS, ICCV, ICLR, ICRA)
Strong intuition for data quality, bias mitigation, and uncertainty modeling
Benefits
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 (available immediately after start date)
AD+D and Life Insurance
Company
Torc Robotics
Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships
501-1000 employees
H1B Sponsorship
Torc Robotics has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (100)
2024 (41)
2023 (33)
2022 (40)
2021 (14)
2020 (7)
Funding
Current Stage
Late StageTotal Funding
unknown2019-03-29Acquired
Leadership Team
Peter Vaughan Schmidt
CEO
April Alexander
Human Resources Business Partner
Recent News
2025-12-02
2025-09-12
2025-09-09
Company data provided by crunchbase