Torc Robotics
ML Engineer, II - Perception
$153K–$184K
Remote - US, Ann Arbor, MI +1 · Remote · Full-time · Posted Aug 7, 2026
- Location
- Remote - US, Ann Arbor, MI
Remote - US - Experience
- 4+ years with a bachelor’s degree, or 0-3+ years with a master’s degree, as stated.
- Education
- Bachelor’s or Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field.
About the job
Embeds with Autonomy teams to integrate and scale model replay, recompute, evaluation, and visualization workflows on Torc Sim.
What you'll do
- Implement data flows across data operations, simulation, and persistent storage; onboard models to replay/recompute and metric evaluation.
- Debug end-to-end issues and integrate model workflows with Torc Sim.
- Drive platform adoption, document workflows, and translate Autonomy team feedback into product improvements.
What they ask for
- Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus competences and technical proficiencies typically acquired through 4+ years of experience, or Master’s Degree in a related technical field plus competences and technical proficiencies typically acquired through 0-3+ years of experience.
- Strong Python skills and experience building or operating data pipelines at scale.
- Experience working with simulation, replay, or model validation.
- Familiarity with autonomy or robotics ML models and their data; comfort working across cloud storage and compute.
Nice to have
- Prior experience in a forward-deployed engineer, solutions engineer, or embedded platform role.
- Experience with autonomous-vehicle or robotics simulation/replay frameworks, visualization tooling, sensor data formats, distributed compute, infrastructure-as-code, or CI systems.
Pay
$153,200 — $183,800 USD (base salary; US Pay Range)
Tools
Python, Foxglove, OpenGL, Three.js, MCAP, Parquet, PyArrow, Ray
AI focus
Supports autonomy ML models by scaling their simulation replay/recompute workflows and evaluating model metrics.
Model-written summary · the original posting is authoritative