FieldAI · 12 hours ago
1.51 Robotics Autonomy Engineer - Locomotion
Irvine, CA
Full-time
Onsite
Entry, Mid Level
2+ years expField AI is transforming how robots interact with the real world by building risk-aware, reliable, and field-ready AI systems. As a Robotics Autonomy Engineer – Locomotion, you will lead the development of reinforcement learning-based controllers for legged and humanoid robots, working closely with a technical team to advance robotic capabilities through research and field validation.
Enterprise SoftwareRobotic Process Automation (RPA)Robotics
Responsibilities
Design RL-Based Locomotion Control Pipelines
Architect and implement scalable reinforcement learning (RL) pipelines optimized for locomotion and manipulation
Integrate physics-based simulation environments (Isaac Gym, Isaac Lab, MuJoCo) with custom training workflows
Optimize reward functions, policy architectures, and sim-to-real transfer methods
Develop and Test Locomotion Behaviors
Create agile and robust policies for legged or humanoid robots in simulated and real-world conditions
Solve challenges in balance, contact-rich dynamics, and high-DOF coordination
Drive iterative testing across terrain variability and unstructured environments
Own Simulation and Evaluation Environments
Build scalable training environments using Isaac Sim and Isaac Gym
Automate evaluation across domain-randomized scenarios and domain adaptation protocols
Maintain high-performance simulation infrastructure for rapid prototyping and validation
Collaborate Across Perception, Planning, and Hardware Teams
Work closely with systems engineers, perception experts, and embedded teams to close the loop between learning and execution
Incorporate real-world telemetry to refine models and improve generalization
Lead deployment workflows from experiment to field robot testing
Qualification
Required
Master's degree or higher in Robotics, Computer Science, Engineering, or related field (PhD a strong plus)
Deep expertise in reinforcement learning, especially for continuous control tasks
2+ years of experience developing and deploying locomotion policies for robotic systems
Proficiency with simulation tools such as Isaac Gym, Isaac Lab, MuJoCo, or PyBullet
Strong understanding of contact dynamics, control theory, and kinematics
Experience with legged and/or humanoid robots (quadrupeds, bipedal systems, or exoskeletons)
Solid Python and/or C++ development skills in Linux-based environments
Familiarity with machine learning frameworks (PyTorch, TensorFlow)
Preferred
3+ years of experience in an industry or startup robotics setting
Experience with real-world deployment of learned locomotion controllers
Publications or open-source contributions in locomotion, RL, or control
Familiarity with ROS or custom middleware for real-time control
Background in manipulation or whole-body coordination
Experience of deploying neural network models on robotic platforms
Experience debugging sim-to-real issues at scale
Contributions to reinforcement learning libraries or simulation platforms
Prior work on multi-agent learning or terrain-adaptive control systems
Company
FieldAI
FieldAI is pioneering the development of a field-proven, hardware agnostic brain technology that enables many different types of robots to operate autonomously in hazardous, offroad, and potentially harsh industrial settings – all without GPS, maps, or any pre-programmed routes.
11-50 employees
H1B Sponsorship
FieldAI has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (9)
Funding
Current Stage
Early StageTotal Funding
$405M2025-08-20Series Unknown· $91M
2025-08-20Series A· $314M
Leadership Team
Ali Agha
Founder and CEO
Recent News
Crunchbase News
2025-12-19
2025-10-16
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