# Senior, ML Engineer - Auto Tagging

Hiring organization: [Torc Robotics](https://career.thegoodapps.co/organizations/torc-robotics)

Canonical page: https://career.thegoodapps.co/jobs/bccf6f27-d4d3-4d99-b61a-72cb2d72a635

Listed on Torc Robotics's own careers site. Applications go to them directly.

- Employment type: full time
- Seniority: Senior
- Location: Ann Arbor, MI
- Remote: yes
- Salary: 177300 – 212800 USD per year

## Summary

This role leads the development of large-scale data pipelines and machine learning systems that extract and categorize safety-critical events from autonomous vehicle sensor logs, feeding a curated library that accelerates perception and simulation across the company. You'll architect distributed systems for petabyte-scale multi-modal data processing, mentor junior engineers, and collaborate cross-functionally to define what scenarios matter most for safe autonomous trucking.

_Our summary, not Torc Robotics's wording._

## Skills named

Amazon Web Services (AWS), Apache Beam, Apache Spark, Databricks, Machine Learning, Microsoft Azure, Python, Robot Operating System (ROS), SQL, V-Ray, Vector Databases

## Required

- BS or MS in Computer Science, Robotics, Engineering, or STEM field
- 6+ years in data engineering, ML systems, or autonomous data curation
- Strong Python and SQL skills with experience on massive time-series or unstructured datasets
- Hands-on machine learning and dataset curation with track record of improving downstream model performance
- Experience with Databricks or similar platforms for large-scale analytics
- Expertise in distributed compute frameworks like Spark, Ray, or Beam
- Experience with AWS, GCP, or Azure for heavy data workloads
- Experience parsing complex data formats and applying Pegasus layer standards
- Exceptional communication and ability to translate data engineering challenges for cross-functional stakeholders
- Proven track record of mentoring teams and driving system architecture

## Nice to have

- Familiarity with foundational models, auto-labeling pipelines, or zero-shot classification
- Experience with vLLM, SGLang, or similar high-throughput model serving frameworks
- Experience with semantic extraction and attribute mapping for semantic inference engines
- Familiarity with parsing robotics formats like ROS bags and MCAP
- Knowledge of how scenario data feeds into generative simulation, neural rendering, or sensor fusion validation
- Experience building semantic retrieval systems or vector databases for automotive data

Apply on Torc Robotics's site: https://job-boards.greenhouse.io/torcrobotics/jobs/8554970002