Lead Robotics Control & Safety Research Engineer

Arm Limited; Austin (TX); Hybrid; USD 250,000 - 338,000; Full time

Benefits offered by this job

Accommodations during recruitment

Hybrid working

Equal opportunities

Job summary

Arm Limited is building a new robotics research lab in Austin focused on embodied AI and real-time control. The role centers on developing control algorithms, integrating learning-based components, and enforcing safety within hierarchical architectures for deployable robotic systems.

We seek experts in control theory, robotics dynamics, and optimization who can design runtime assurance, handle latency constraints, and contribute to cross-disciplinary system integration across ML, perception, and

Qualifications

• Strong background in control theory, robotics dynamics, optimization.
• Experience with real-time or safety-critical systems.
• Proficiency in C++ and/or Python.
• Experience with robotic platforms and simulators.
• Publications in top-tier venues.

Responsibilities

• Develop control algorithms (e.g., MPC, optimal control) for complex robots.
• Integrate control with learning-based components in hierarchical systems.
• Design safety mechanisms (runtime assurance, constraint enforcement).
• Contribute to real-time system design under strict latency constraints.
• Enable system-level integration across ML, perception, and systems.
• Translate safety and control requirements into compute and architecture insights.

Skills

Control theory

Robotics dynamics

Optimization

Real-time / safety-critical systems

C++ / Python

Robotic platforms

Robotics simulators

Publications in top venues

Job description

Arm Limited is building a new robotics research lab in Austin focused on embodied AI and real-time control. The role centers on developing control algorithms, integrating learning-based components, and enforcing safety within hierarchical architectures for deployable robotic systems.

We seek experts in control theory, robotics dynamics, and optimization who can design runtime assurance, handle latency constraints, and contribute to cross-disciplinary system integration across ML, perception, and