Torc Robotics
Senior, ML Engineer - VLM
$177K–$213K
Ann Arbor, MI, Remote - US +1 · Remote · Senior · Full-time · Posted Jul 8, 2026
- Location
- Ann Arbor, MI, Remote - US
Ann Arbor, Michigan, United States - Experience
- Bachelor’s degree plus 6+ years of experience, or Master’s degree plus 3+ years of experience.
- Education
- Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering, or related technical field; OR Master’s Degree in a related technical field.
About the job
Owns the cloud-based data pipelines and curated datasets used to train and evaluate vision-language-action models for autonomous trucks.
What you'll do
- Build and operate pipelines that transform logged sensor data into geometric, semantic, and trajectory-grounded training labels.
- Develop VLM-assisted auto-labeling and curate rare or difficult scenarios to improve downstream model performance.
- Set dataset schemas and quality standards, close the data flywheel with model teams, and lead and mentor engineers.
What they ask for
- Computer vision and deep learning model training, plus experience in at least two listed perception areas (such as detection, tracking, sensor fusion, segmentation, BEV, or depth estimation).
- Hands-on multimodal/VLM experience applied to perception data.
- Experience building targeted model-training datasets and processing large-scale Parquet data.
- Strong Python development and experience with distributed ML/data frameworks and MLOps tooling.
Nice to have
- Familiarity with VLM/VLA or end-to-end driving models, trajectory/action grounding, or reasoning-trace datasets.
- Experience with auto-labeling foundation models, high-throughput serving, or cloud orchestration.
Pay
$177,300 — $212,800 USD (total pay)
Tools
Python, Parquet, PyTorch, Lightning, Ray, Spark, MLflow, Docker
AI focus
Build VLM/VLA training datasets and foundation-model-assisted auto-labeling, including language-grounded reasoning and trajectory annotations for autonomous driving.
Model-written summary · the original posting is authoritative