Drimva

Torc Robotics

Senior, Software Engineer - AutoTagging

$161K–$193K

Ann Arbor, MI, Remote - US +1 · Remote · Senior · Full-time · Posted Aug 10, 2026

Location
Ann Arbor, MI, Remote - US
Ann Arbor, Michigan, United States
Experience
6+ years with a bachelor’s degree, or 3+ years with a master’s degree.
Education
Bachelor’s or master’s degree in Computer Science, Robotics, Electrical Engineering, or a related technical field.

About the job

Build and operate scalable algorithms that identify and evaluate driving scenarios in autonomous-truck sensor data.

What you'll do

  • Design and implement event-detection algorithms for multi-sensor time-series data, combining rule-based methods with learned components where appropriate.
  • Create ground-truth evaluation, scenario metrics, failure analysis, and regression tests for tagger quality.
  • Deploy and optimize production taggers on Databricks/Spark, including CI and monitoring across large vehicle-data logs.

What they ask for

  • Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, or related technical field plus 6+ years of experience; or a master’s degree in one of these fields plus 3+ years of experience.
  • Demonstrated algorithm-design experience with real-world sensor, time-series, or geospatial data.
  • Strong Python skills, including NumPy, pandas, and SciPy, and working proficiency in SQL.
  • Experience evaluating algorithm quality against labeled or ground-truth data; hands-on exposure to distributed compute, a cloud platform, and CI/CD.

Nice to have

  • Autonomous-vehicle or robotics data experience, including ROS bags/MCAP, HD maps, or lane-relative coordinates.
  • Experience with VLMs, auto-labeling, scenario standards, infrastructure-as-code, observability, model serving, or columnar storage formats.

Pay

$160,800 — $193,000 USD (base salary)

Tools

Python, NumPy, pandas, SciPy, SQL, Spark, Ray, Databricks

AI focus

Use learned components such as classifiers, embeddings, and Vision-Language Models alongside rule-based event detection for scenario extraction.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 4, 2026 (UTC)