Skip to main content

Field AI

Robotics Autonomy Engineer - Manipulation

Irvine, CAfull timemidAdded 6 days ago

About this role

FieldAI is seeking a Robotics Autonomy Engineer focused on manipulation to develop risk-aware, field-ready AI systems for real robot deployments in Southern California. You'll combine rigorous engineering with learning systems, moving beyond standard approaches to create solutions that improve through real-world robot operations.

What you'll do

  • Design and implement autonomous manipulation algorithms for field-deployed robotic systems
  • Develop risk-aware control systems that balance performance with safety and reliability
  • Integrate perception, planning, and learning components for embodied AI applications
  • Conduct hardware testing and iterate on solutions based on real deployment feedback
  • Collaborate with cross-functional teams to solve complex robotics challenges
  • Optimize systems for real-world environmental conditions and operational constraints

What they're looking for

  • Robotics manipulation and control systems
  • Autonomous systems and path planning
  • Machine learning and learning-based control
  • Sensor integration and perception
  • Software engineering and systems integration
  • Hardware testing and debugging
  • Python or C++ programming
  • Risk assessment and safety engineering
Apply with Autofill

Opens the application — the Jobs AI extension fills it for you. Set up autofill

Opens the official application on the employer’s site. No login required.

Field AI

Field AI develops embodied AI and autonomous robotics systems for real-world deployment in industrial environments like oil & gas and mining. The company is hiring software engineers to build web-based systems, perception and validation pipelines, test infrastructure, ROS-based robotic software, and customer-facing products that integrate AI with field-deployed hardware.

View all jobs at Field AI

Likely interview questions

  • Describe your experience developing autonomous systems that operate in real-world, unstructured environments.
  • How have you approached balancing data-driven learning with deterministic control in robotics applications?
Unlock all 7 questions free — and practice them live →