Autonomy Controls Engineer for Legged Robots (Python)

Fluency Digital, Inc.; Los Angeles (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Fluency Digital, Inc. is seeking an engineer who enjoys elegant six‑legged gait cycles and autonomous robots. You will craft Python control stacks enabling bio‑inspired hardware to operate autonomously in complex industrial settings and space‑forward environments.

This is a rare chance to shape locomotion logic from the ground up within a mission‑focused team. You will translate high‑level autonomy ideas into robust motion planning, state estimation, and feedback control for real‑world hardware,

Qualifications

• 5–10 years hands-on experience developing control systems for dynamic legged robots or multi‑contact platforms.
• Deep proficiency in Python for implementing real‑time motion planning, state estimation, and feedback control loops.
• Proven ability to bridge the gap between high‑level autonomy algorithms and low‑level hardware actuation on physical systems.
• A practical mindset geared toward solving novel mechanical challenges in unstructured, high‑stakes environments.
• Must be based in the United States.

Responsibilities

• Develop robust Python control stacks for autonomous legged robots.
• Implement real‑time motion planning and state estimation.
• Bridge high‑level autonomy with low‑level hardware actuation on physical systems.
• Tackle novel mechanical challenges in unstructured, high‑stakes environments.

Skills

Python

Control systems

Motion planning

State estimation

Real-time control

Hardware integration

Autonomy algorithms

Job description

Fluency Digital, Inc. is seeking an engineer who enjoys elegant six‑legged gait cycles and autonomous robots. You will craft Python control stacks enabling bio‑inspired hardware to operate autonomously in complex industrial settings and space‑forward environments.

This is a rare chance to shape locomotion logic from the ground up within a mission‑focused team. You will translate high‑level autonomy ideas into robust motion planning, state estimation, and feedback control for real‑world hardware,