MLOps Engineer - Pipelines & Debugging

Torc; United States; Remote; USD 120,000 - 150,000; Full time

Benefits offered by this job

Stock options

Bonus component

Medical/dental/vision coverage

401K with employer match

Paid vacation

Job summary

Torc is shaping the future of autonomous trucking with a focus on software for automated trucks. As a Machine Learning Engineer on the ML Ops Framework & Conversion team, you will support model development pipelines, triage issues, and help scale our infrastructure for reliable deployment across the ML stack.

You’ll work with engineers across ML and embedded systems, gain broad exposure to cutting-edge model infrastructure, and contribute to tooling, documentation, and processes that keep

Qualifications

• BS in Computer Science, Robotics, Electrical Engineering or related field.
• Proficiency in Python and ML frameworks (PyTorch).
• Experience with MLOps tooling, CI/CD, monitoring and pipelines.
• Strong debugging and cross-team communication.

Responsibilities

• Provide on-call MLOps support for model development teams.
• Debug model development workflows and identify root causes.
• Collaborate with senior engineers to improve tooling and processes.
• Communicate findings across the organization.

Skills

Python

PyTorch

CI/CD

Monitoring

Logging

Pipeline orchestration

Debugging

Communication

Education

Bachelor's degree in Computer Science, Robotics, Electrical Engineering or related field

Tools

PyArrow

Parquet

MCAP

Daft

Pandas

Ray

Anyscale

AWS Sagemaker

Terraform

Job description

Torc is shaping the future of autonomous trucking with a focus on software for automated trucks. As a Machine Learning Engineer on the ML Ops Framework & Conversion team, you will support model development pipelines, triage issues, and help scale our infrastructure for reliable deployment across the ML stack.

You’ll work with engineers across ML and embedded systems, gain broad exposure to cutting-edge model infrastructure, and contribute to tooling, documentation, and processes that keep