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ML Engineer, I - MLOps Framework

Full-time Remote work

Publication date: 30/08/2026

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. 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.

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

Requirements

Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 0-3+ years of 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 have

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

Benefits

A 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
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