Senior ML Engineer - Auto Tagger

Salary: $177,300 - 212,800 per year Requirements:

• We require a BS or MS in Computer Science, Robotics, Engineering, or a STEM discipline, along with 6+ years of experience in data engineering, ML systems, or autonomous data curation.
• We look for strong Python and SQL skills, with substantial experience working on massive time-series or unstructured datasets.
• We want hands-on machine learning and dataset curation experience, including a track record of building targeted datasets that improve downstream model performance.
• We value experience with Databricks or similar tools for large-scale analytics, interactive querying, and making large vehicle datasets searchable.
• We need expertise with distributed compute frameworks such as Ray, Spark, or Beam, as well as cloud platforms like AWS, Google Cloud Platform, or Azure.
• We expect experience parsing complex data structures and applying scenario-description standards such as Pegasus layers.
• We need strong communication skills with the ability to explain complex data engineering issues and strategies to cross-functional partners.
• We look for proven technical leadership, including mentoring teams, shaping system architecture, and defining engineering roadmaps.
• Bonus: familiarity with foundation models, auto-labeling pipelines, or zero-shot classification for scenario extraction.
• Bonus: experience with vLLM, SGLang, or similar frameworks for high-throughput model serving and inference.
• Bonus: experience with semantic extraction and attribute mapping beyond standard bounding-box object detection.
• Bonus: familiarity with ROS bags, MCAP, Parquet, or Arrow.
• Bonus: knowledge of how scenario data supports generative simulation, neural rendering, or sensor fusion validation.
• Bonus: experience building semantic retrieval systems or vector databases for automotive data.

• We architect and refine distributed data pipelines that process large multi-sensor logs, automatically identifying and cataloging safety-critical and long-tail driving events.
• We develop and tune heuristic and ML-assisted tagging methods, including exploring vision-language models or semantic vector search, to classify and describe complex scenarios.
• We structure and standardize scenario data using the Pegasus layer standard and related open-source tools to maintain semantic consistency and accurate metadata.
• We manage ingestion of tagged events into our observations database so teams can query and retrieve data quickly for model training, regression testing, and system validation.
• We collaborate closely with perception, simulation, and systems engineering partners to define interesting scenarios and sustain a continuous data loop.
• We work with broad autonomy to align stakeholders across the organization and drive agreement on data definitions and priorities.
• We mentor less-experienced engineers, lead design reviews, set coding standards, and promote technical excellence and collaborative problem-solving.

• AWS
• Architect
• Azure
• Cloud
• Databricks
• Support
• LESS
• Machine Learning
• Model Serving
• Model Training
• Python
• ROS
• Robotics
• SQL
• Sensor Fusion
• Spark
• vLLM
• DevOps

More:

We are Torc, a leader in autonomous driving since 2007 and now part of the Daimler family, focused on developing software for automated trucks that will transform freight movement. Our Auto Tagger team powers our data flywheel by turning petabytes of raw, multi-modal vehicle data into a curated library of critical driving scenarios, enabling safer autonomous trucking and accelerating work across perception, sensor fusion, and generative simulation testing. We offer a collaborative, energetic, team-focused culture, plus a competitive compensation package with bonus and stock options, fully paid medical, dental, and vision premiums for full-time employees, a 401K with 6% employer match, flexible scheduling, generous paid vacation, company-wide holiday closures, and AD&D and life insurance. We are committed to building a diverse and inclusive workplace and encourage candidates to apply even if they do not meet every qualification. The hiring range for this role is $177,300 to $212,800 USD in the US, with total compensation potentially including sign-on payments, relocation support, and other benefits depending on the position and market.

last updated 33 week of 2026