ML Engineer, New AI Initiatives for Autonomous Trucks

Torc Robotics; United States; Remote; USD 153,000 - 184,000; Full time

Benefits offered by this job

Bonus + stock

Health/dental/vision

401K match

Flexible schedule

Paid vacation

AD&D insurance

Job summary

Torc is seeking a Machine Learning Engineer to translate ambiguous problems into scalable ML workflows and production-ready solutions. You will join the ML Ops team, applying data science methods and software discipline to deliver robust AI tooling.

In this role you’ll work with Data Ops on ingestion, governance, and data prep while leading projects and mentoring peers. Emphasis on rigorous deployment, cross-team communication, and real-world impact.

Qualifications

• Bachelor's degree in Computer Science, Robotics, Electrical Engineering or related technical field.
• Master’s degree in CS/Robotics/EE with up to 3+ years of experience.
• Willingness to work on frontier topics and communicate outcomes across teams.

Responsibilities

• Build the foundation of Torc's AI development tooling.
• Develop data science models or algorithms with disciplined software practices.
• Collaborate with Data Ops on data ingestion, preparation, curation, and governance.
• Organize and lead projects, guiding junior engineers in project execution.
• Empower users with insights, enabling data accessibility for stakeholders.
• Develop guidelines for analytics and model deployment processes.
• Communicate progress with team interfaces across the organization.

Skills

Data science

Machine learning

Python

Model deployment

Data governance

Education

BSc in CS/Robotics/EE

MSc in CS/Robotics/EE

Tools

Git

TensorFlow

PyTorch

SQL

Job description

Torc is seeking a Machine Learning Engineer to translate ambiguous problems into scalable ML workflows and production-ready solutions. You will join the ML Ops team, applying data science methods and software discipline to deliver robust AI tooling.

In this role you’ll work with Data Ops on ingestion, governance, and data prep while leading projects and mentoring peers. Emphasis on rigorous deployment, cross-team communication, and real-world impact.