Senior ML Data Delivery Engineer

Torc Robotics; Ann Arbor (MI); On-site; USD 161,000 - 193,000; Full time

Benefits offered by this job

Bonus + stock options

Medical, dental, vision covered

401K with 6% match

Flexible schedule

Holiday office closures

AD&D and life insurance

Job summary

Torc Robotics is seeking an experienced data/ML pipeline engineer to design, build, and improve tooling for pseudo-labeled data and ML training workflows. You will ensure data quality and deliver reliable data to model training in a fast-growing autonomous trucking environment.

The role emphasizes Python development, distributed systems, and collaboration with perception teams to advance offline and online data infrastructure for autonomous driving.

Qualifications

• Bachelor's or Master’s in CS, robotics, or electrical engineering with relevant experience.
• Strong background in data pipelines, ML ops, and distributed systems.
• Proven Python software development and cloud/CI/CD experience.

Responsibilities

• Design, implement, test, and deploy tooling for quality control of pseudo-labeled data.
• Provide statistics on data quality, coverage, and pipeline health for stakeholders.
• Support data selection and on-demand data provisioning for model training.
• Develop ML data delivery systems enabling on-demand model training.
• Lead projects and mentor junior engineers while improving pipelines.

Skills

Software engineering

Data pipelines

MLOps

Python

Distributed systems

Team mentoring

Project leadership

Education

Bachelor's in CS/Robotics/EE

Master's in CS/Robotics/EE

Tools

Python

PyTorch

PyArrow

Daft

Pandas

Docker

GitHub Actions

MLflow

Weights & Biases

Job description

Torc Robotics is seeking an experienced data/ML pipeline engineer to design, build, and improve tooling for pseudo-labeled data and ML training workflows. You will ensure data quality and deliver reliable data to model training in a fast-growing autonomous trucking environment.

The role emphasizes Python development, distributed systems, and collaboration with perception teams to advance offline and online data infrastructure for autonomous driving.