Field Robotics Automation Engineer & ML Specialist

FieldAI; Irvine (CA); On-site; USD 110,000 - 140,000; Full time

Job summary

FieldAI in Irvine is seeking an Automation Engineer to improve reliability and performance of deployed robot fleets across real-world sites. You will work at the intersection of robotics, machine learning, and field operations, owning triage and resolution of autonomy issues.

This role involves hands-on ML work, building datasets, training and fine-tuning models, and collaborating with deployment teams to validate improvements on robots, ensuring stable operation across sites.

Qualifications

• Bachelor’s or Master’s degree in CS, robotics, AI, or related field.
• Strong Python and experience with ML frameworks such as PyTorch.
• Experience training, fine-tuning, and evaluating ML models.
• Strong debugging and problem-solving skills across ML and robotics systems.
• Experience with C++ and production ML/robotics systems.
• Understanding of ML data pipelines, labeling, evaluation, and model deployment.
• Interest or experience in robotics, autonomous systems, perception, prediction, or planning.
• Ability to work across modeling, data/labeling, and deployment teams.

Responsibilities

• Site performance triage and resolve issues across deployed sites.
• Analyze robot behavior, logs, telemetry, and model outputs.
• Build datasets and evaluation sets for new failure modes.
• Train, fine-tune, and evaluate ML models as needed.
• Partner with deployment and robotics engineers to validate improvements.
• Support new use cases from development through production deployment.

Skills

Python

PyTorch

C++

Machine Learning

Robotics

Data pipelines

Debugging

Problem solving

Education

Bachelor’s or Master’s in CS/Robotics/AI

Job description

FieldAI in Irvine is seeking an Automation Engineer to improve reliability and performance of deployed robot fleets across real-world sites. You will work at the intersection of robotics, machine learning, and field operations, owning triage and resolution of autonomy issues.

This role involves hands-on ML work, building datasets, training and fine-tuning models, and collaborating with deployment teams to validate improvements on robots, ensuring stable operation across sites.