ML Engineer, I - MLOps Framework

Role overview

This is an early-career MLOps engineering role supporting the day-to-day operations of an autonomous trucking model development ecosystem. The position focuses on keeping ML pipelines healthy, triaging issues across the ML stack, and helping engineers ship models from research into production reliably and at scale.

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 with model development teams and broader stakeholders to ensure issues are resolved quickly and findings are shared across the organization.

Requirements

- Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or a related technical field, with 0-3+ years of relevant experience. - Proficiency in Python and foundational experience with ML frameworks such as PyTorch, plus familiarity with model training pipelines. - Experience with MLOps tooling including CI/CD systems, monitoring, logging, and pipeline orchestration. - Strong debugging and problem-solving skills with the ability to triage issues under pressure. - Clear communication skills and the ability to translate technical issues for different audiences.

Nice to have

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

Benefits and work setup

- US hiring range of $132,400 to $158,900, plus bonus and stock options. - 100% employer-paid medical, dental, and vision premiums for full-time employees. - 401K plan with a 6% employer match. - Flexible scheduling with generous paid vacation available from start date. - AD+D and life insurance coverage.