Senior Machine Learning Engineer - Auto Tagging

Skills

About the Role

You will build distributed pipelines that process vehicle data and identify safety-critical driving scenarios. You will develop automated tagging algorithms, structure scenario data, manage database ingestion, collaborate with downstream users, and mentor engineers.

Requirements

• Bachelor's or master's degree in a STEM field and 6+ years of data engineering, ML systems, or autonomous data-curation experience.
• Strong Python and SQL skills.
• Machine learning and dataset-curation experience.
• Databricks or similar large-scale analytics platform experience.
• Distributed compute experience with Ray, Spark, or Beam.
• Cloud-platform experience with AWS, GCP, or Azure.
• Experience parsing complex data formats and applying Pegasus layers.
• Technical leadership, architecture, roadmap, mentoring, and stakeholder communication experience.

Responsibilities

• Architect and optimize distributed pipelines for multi-sensor vehicle logs.
• Extract and catalog safety-critical and long-tail driving events.
• Develop heuristic-based and ML-assisted event-tagging algorithms.
• Classify and describe environmental and behavioral scenarios.
• Format scenario data using Pegasus layer standards.
• Manage ingestion of tagged events into the observations database.
• Define interesting scenarios with perception, simulation, and systems engineering stakeholders.
• Mentor engineers, lead design reviews, and establish coding standards.

Benefits

• Bonus component and stock options.
• 100% paid medical, dental, and vision premiums for full-time employees.
• 401K plan with a 6% employer match.
• Flexible schedule and generous paid vacation available immediately after start date.
• Company-wide holiday office closures.
• AD+D and life insurance.