Senior, ML Engineer - Auto Tagging
$177k - $213k • Remote • Ann Arbor, MI, Remote - US • Full-time
Posted 5mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Ann Arbor, MI, Remote - US
Tech Stack
Remote Work Policy
Fully remote
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
The Auto Tagger team is central to our data operations, responsible for transforming vast amounts of raw vehicle data into a curated library of critical driving scenarios. By identifying long-tail events within driving logs, this team provides essential data to accelerate the development of safe autonomous trucking. They structure and catalog findings into an observations database, directly supporting advancements in autonomous perception, sensor fusion, and generative simulation testing.
Responsibilities
- Architect and optimize distributed data pipelines to process multi-sensor logs and automatically extract/catalog driving events.
- Develop and tune heuristic-based and ML-assisted algorithms for classifying complex environmental and behavioral scenarios.
- Extract and format scenario data according to Pegasus layer standards and open-source frameworks for consistency and metadata integrity.
- Manage the ingestion of tagged events into the observations database for querying and retrieval.
- Collaborate with perception, simulation, and systems engineering teams to define 'interesting scenarios' and operationalize a data loop.
- Mentor junior engineers, lead design reviews, and establish coding standards.
Requirements
- Bachelor's degree in Computer Science, Robotics, Electrical Engineering or related field with 6+ years of experience, OR Master's with 3+ years, OR PhD with 1+ year.
- Strong Python and SQL skills, with experience processing large time-series or unstructured datasets.
- Hands-on machine learning and dataset curation experience, with a history of improving downstream model performance.
- Experience using Databricks (or similar) for large-scale analytics and interactive querying.
- Expertise in distributed compute frameworks (Ray, Spark, Beam) and cloud platforms (AWS, GCP, Azure).
- Experience parsing complex data formats and applying scenario-description standards like Pegasus layers.
- Exceptional ability to communicate complex data engineering challenges to cross-functional stakeholders.
- Proven track record of mentoring teams, driving system architecture, and defining engineering roadmaps.
Benefits
- Competitive compensation package with 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
- Company-wide holiday office closures
- AD+D and Life Insurance