ML Ops Engineer I - Build Scalable ML Pipelines

Torc Robotics; United States; On-site; USD 132,000 - 159,000; Full time

Benefits offered by this job

Bonus + stock options

100% medical, dental, vision premiums

401K with 6% match

Flexible schedule & generous vacation

AD+D and Life Insurance

Job summary

Torc Robotics in the United States is seeking a Machine Learning Engineer to join the ML Ops Framework & Conversion team. You will support model development pipelines, triage issues, and help scale tooling for autonomous-trucking software.

The role requires a BS in CS/Robotics/EE, strong Python skills, and experience with ML frameworks like PyTorch and MLOps tooling. You will collaborate across teams and contribute to robust, scalable ML workflows.

Qualifications

• BS in Computer Science, Robotics, Electrical Engineering or related field; 0–3+ years of experience.
• Proficiency in Python and ML frameworks such as PyTorch; familiarity with model training pipelines.
• Experience with MLOps tooling including CI/CD, monitoring, logging, and orchestration.

Responsibilities

• Provide on-call MLOps support for model development teams and triage pipeline issues.
• Assist in debugging model development workflows and identify root causes across the ML stack.
• Collaborate with senior engineers to improve tooling, documentation, and processes.
• Communicate findings clearly to model development teams and stakeholders.

Skills

Python

PyTorch

ML pipelines

MLOps tooling

CI/CD

Debugging

Cross-team communication

Education

Bachelor’s Degree in Computer Science/Robotics/Electrical Engineering or related technical field

Tools

CI/CD tooling

Monitoring

Logging

Pipeline orchestration

Ray / AWS Sagemaker

Job description

Torc Robotics in the United States is seeking a Machine Learning Engineer to join the ML Ops Framework & Conversion team. You will support model development pipelines, triage issues, and help scale tooling for autonomous-trucking software.

The role requires a BS in CS/Robotics/EE, strong Python skills, and experience with ML frameworks like PyTorch and MLOps tooling. You will collaborate across teams and contribute to robust, scalable ML workflows.