Senior ML Data Delivery Engineer - Pseudo-Labeling

Socket.dev; Ann Arbor (MI); Hybrid; USD 161,000 - 193,000; Full time

Benefits offered by this job

Stock options

Medical, dental, vision premiums paid

401K with match

Generous vacation

Holiday closures

AD+D and Life Insurance

Job summary

Torc is seeking a senior data/ML engineer to design, implement, and optimize data pipelines for pseudo-labeling and on-demand model training. You will ensure data quality, scale, and reliability across the data delivery stack, collaborating with perception and analytics teams.

You will lead tooling development, mentor teammates, and help shape the offline perception and ML infrastructure used in autonomous driving. This role offers a competitive package and stock options.

Qualifications

• Bachelor’s or Master’s degree in a related field with extensive relevant experience.
• Strong software engineering background building and operating data pipelines at scale.
• Experience with ML Ops, model registry, experiment tracking, and data quality metrics.

Responsibilities

• Design and deploy tooling for quality control of pseudo-labeled data for model training.
• Provide reporting on data quality, coverage, and pipeline health to stakeholders.
• Support data selection and on-demand data delivery for model training pipelines.
• Lead data pipeline improvements to increase throughput and reliability.
• Mentor engineers and drive project execution across the team.

Skills

Python

Data pipelines

ML Ops

Distributed processing

PyTorch

Docker

GitHub Actions

Weights & Biases

Pandas

Parquet

Education

Bachelor’s Degree in CS/Robotics/EE

Master’s Degree in CS/Robotics/EE

Tools

PyArrow

Daft

Pandas

Parquet

Job description

Torc is seeking a senior data/ML engineer to design, implement, and optimize data pipelines for pseudo-labeling and on-demand model training. You will ensure data quality, scale, and reliability across the data delivery stack, collaborating with perception and analytics teams.

You will lead tooling development, mentor teammates, and help shape the offline perception and ML infrastructure used in autonomous driving. This role offers a competitive package and stock options.