ML Engineer, I - MLOps Framework

Summary

Torc Robotics develops software for automated trucks and autonomous driving systems. The ML Engineer will support MLOps operations for model development teams by triaging pipeline issues, debugging workflows, and improving tooling and operational processes across the machine learning stack.

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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

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
• Generous paid vacation (available immediately after start date)
• AD+D and Life Insurance