ML Engineer, I - MLOps Framework

Torc Robotics
$132,400

About The Position

As a Machine Learning Engineer on the ML Ops Framework & Conversion team, you will support the day-to-day operations that keep Torc's model development ecosystem running smoothly. Our team is comprised of engineers with deep expertise in ML and RL frameworks, embedded systems, and autonomous driving — united by a focus on getting models from development into the real world reliably and at scale. In this role, you will provide general MLOps support to model development teams, helping triage issues, maintain pipelines, and ensure engineers have what they need to move fast. You'll gain broad exposure across the ML stack and grow alongside a team working on some of the most complex model infrastructure in autonomous trucking.

Requirements

  • Bachelor's Degree in Computer Science, Electrical Engineering, Robotics, or related field plus 1+ years of relevant experience; or equivalent practical experience.
  • Proficiency in Python, with foundational experience in ML frameworks such as PyTorch and familiarity with model training pipelines.
  • Experience with MLOps tooling — CI/CD systems, monitoring, logging, and pipeline orchestration.
  • Strong debugging and problem-solving skills with an ability to triage issues under pressure.
  • Clear communicator who can work across teams and translate technical issues for different audiences.

Nice To Haves

  • Experience with large sensor data formats (MCAP, Parquet) and associated processing tools (PyArrow, Daft, Pandas).
  • Experience with distributed compute/orchestration frameworks (Ray, Anyscale, AWS Sagemaker).
  • Infrastructure-as-code experience (Terraform).
  • Experience with edge deployment or embedded hardware.
  • Exposure to autonomous driving or robotics ML workflows.

Responsibilities

  • Provide on-call MLOps support for model development teams, triaging and resolving pipeline issues as they arise.
  • Assist in debugging model development workflows and identifying root causes across the ML stack.
  • Collaborate with senior engineers to improve tooling, documentation, and operational processes.
  • Communicate and collaborate with model development teams and broader stakeholders, ensuring issues are resolved quickly and findings are shared across the organization.

Benefits

  • Competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • AD+D and Life Insurance
  • Sign-on payments
  • Relocation assistance
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