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TORC Robotics
TORC Robotics

60 Torc Robotics Field Applications Engineer Jobs Hiring Near You

Torc Robotics

Senior, ML Engineer - Auto Tagger

$107K - $146K/yr

Torc Robotics is a leader in autonomous driving technology focused on developing software for ... Required : • BS or MS in Computer Science, Robotics, Engineering, or a STEM field, with 6+ years ...

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102K - $140K/yr

What You'll Need to Succeed: * BS or MS in Computer Science, Robotics, Engineering, or a STEM field ... Perks of Being a Torc'r Torc cares about our team members and we strive to provide benefits and ...

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Infographic showing various Field Applications Engineer job openings at Torc Robotics in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% Physical, and 25% Remote job distribution.

Senior, ML Engineer - Auto Tagger

Torc Robotics

Remote

$107K - $146K/yr

Full-time

Re-posted 23 days ago

Job description

Job Summary:
Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. The Senior ML Engineer - Auto Tagger will be responsible for architecting data pipelines and developing algorithms to optimize the processing of vehicle data, ensuring data integrity and facilitating collaboration across teams.
Responsibilities:
• Architect and optimize distributed data pipelines to process massive multi-sensor logs (camera, LiDAR, radar, kinematics), automatically extracting and cataloging safety-critical and long-tail driving events.
• Develop and tune both heuristic-based and ML-assisted algorithms (including exploring Vision-Language Models or semantic vector search) to automatically classify and describe complex environmental and behavioral scenarios.
• Extract and format scenario data utilizing the Pegasus layer standard (alongside opensource frameworks) to ensure semantic consistency and rigorous metadata integrity.
• Manage the ingestion of tagged events into the observations database, enabling high-speed querying and retrieval for ML training, regression testing, and system validation.
• Operate with broad autonomy to drive consensus across organizational boundaries.
• Collaborate closely with downstream consumers in perception, simulation, and systems engineering to define what constitutes an 'interesting scenario' and operationalize a continuous data loop.
• Guide, mentor, and elevate less-experienced engineers.
• Lead design reviews, establish coding standards, and foster a culture of technical excellence and collaborative problem-solving.
Qualifications:
Required:
• BS or MS in Computer Science, Robotics, Engineering, or a STEM field, with 6+ years in data engineering, ML systems, or autonomous data curation.
• Strong Python and SQL skills, with heavy experience processing massive time-series or unstructured datasets.
• Hands-on machine learning and dataset curation experience, with a demonstrated history of implementing targeted datasets that measurably improve downstream model performance.
• Hands-on experience using Databricks (or similar platforms) for large-scale analytics, interactive querying, and making massive vehicle datasets searchable.
• Expertise in distributed compute frameworks (Ray, Spark, Beam) and cloud platforms (AWS, GCP, or Azure) for executing heavy data workloads.
• Experience parsing complex data formats and applying scenario-description standards like Pegasus layers.
• Exceptional ability to translate complex data engineering challenges into clear strategies for cross-functional stakeholders.
• Proven track record of mentoring teams, driving system architecture, and defining engineering roadmaps.
Preferred:
• Familiarity with foundational models, auto-labeling pipelines, or zero-shot classification for scenario extraction.
• Experience with vLLM, SGLang, or similar frameworks for highly optimized, high-throughput model serving and inference.
• Experience with semantic extraction and attribute mapping to help build out a robust semantic inference engine, moving beyond standard bounding-box object detection.
• Familiarity with parsing robotics formats (ROS bags, MCAP) and optimizing high-performance columnar storage formats (Parquet, Arrow).
• Knowledge of how scenario data feeds into generative simulation workflows, neural rendering, or sensor fusion validation.
• Experience building semantic retrieval systems or vector databases for automotive data.
Company:
Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships Founded in 2005, the company is headquartered in Blacksburg, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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