Senior Research Scientist: Planning and Control

Holiday Robotics Research Inc. is the US subsidiary of Holiday Robotics, the fastest-growing robotics company in South Korea. We build our systems entirely from scratch - hardware, firmware, low-level controllers, simulators, and end-user software - all in-house, with the goal of freeing humans from tedious, dangerous, and repetitive tasks.

We are looking for a Senior Research Scientist in planning and control to drive the development of motion planning, trajectory optimization, and navigation algorithms for our mobile-based humanoid robot, Friday. You will design computationally efficient, real-time algorithms that enable Friday to safely navigate dynamic, complex environments while executing dexterous manipulation tasks.

You will implement real-time, kinematically feasible motion planning; develop trajectory optimization and predictive control frameworks (e.g., MPC) that ensure dynamic balance under high payloads; and build robust pipelines for dynamic collision avoidance that fuse real-time perception to continuously re-plan on the fly. You will formulate algorithms that coordinate mobile-base navigation with upper-body bimanual manipulation for smooth, safe whole-body motion, validate them in our in-house simulator, and deploy them on physical hardware - working closely with the perception, control, machine learning, hardware, and firmware teams to respect real physical constraints such as actuator limits and communication latencies.

• MS or Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a closely related quantitative field.
• 7+ years of experience (or 5+ years with an advanced degree) in robotics, focusing on motion planning and control for mobile platforms, manipulators, or autonomous vehicles - both custom-built and commercially available systems.
• Deep theoretical and practical understanding of classic and modern planning algorithms (e.g., GCS, RRT*, PRM), trajectory optimization (e.g., Traj Opt), and predictive control (e.g., MPPI).
• Strong background in optimization theory and state estimation, with a deep commitment to mathematical exactness for the governing physical equations.
• Proficiency in AI-assisted coding (e.g., Claude, Codex) to rapidly write, debug, and optimize code, accelerating the transition from research to real-robot deployment.

• Experience with whole-body control architectures or model predictive control on mobile-based humanoid or quadrupedal platforms.
• Experience with machine learning approaches to planning, such as imitation learning or reinforcement learning for trajectory generation and policy synthesis.
• Experience in bimanual manipulation, including object handovers, dual-arm coordination, and impedance/admittance control.
• Experience bridging the sim-to-real gap for complex, long-horizon tasks.

• Base salary range: $200,000 – $250,000 USD annually, commensurate with experience and technical proficiency.
• Competitive equity packages in a rapidly growing, well-funded startup.
• 100% employer-covered health, dental, and vision insurance (full-network PPO).
• Relocation stipend for out-of-state candidates.