Senior, ML Engineer - Auto Tagger
Core
Architect and optimize distributed data pipelines to process massive multi-sensor logs and automatically extract, tag, and catalog safety-critical driving scenarios for autonomous trucking.
Role type
Senior, hands-on IC machine-learning engineer (autonomous data curation)
Builds
A curated library of critical driving scenarios and an observations database for autonomous perception, sensor fusion, and generative simulation testing
Domain
Autonomous driving / Robotics / Data Engineering
Deliverable
production ML models
Required skills
Python, SQL, distributed data pipelines, machine learning, dataset curation, Databricks, Ray, Spark, Beam, AWS/GCP/Azure, Pegasus layers
Preferred skills
Vision-Language Models, semantic vector search, vLLM, SGLang, semantic inference, ROS bags, MCAP, Parquet, Arrow, vector databases
Responsibilities
Architect and optimize distributed data pipelines for massive multi-sensor logs; Develop and tune heuristic-based and ML-assisted algorithms for event tagging; Extract and format scenario data using Pegasus layer standard; Manage ingestion of tagged events into the observations database; Mentor less-experienced engineers and lead design reviews
Seniority
Senior, hands-on IC
