Senior Research Scientist: Planning and Control

Job Title: Senior Research Scientist:

Planning and Control

Company: Holiday Robotics Research Inc.

Location: Mountain View, CA (On-site)

Holiday Robotics Research Inc. is the US subsidiary of Holiday Robotics, the fastest‑growing robotics company in South Korea. After securing $100 million in Series A funding—a historic record in South Korea—we expanded to the US to recruit the industry's top robotics talent. We are working relentlessly to deploy our robots out of controlled lab environments, with the ultimate goal of freeing humans from tedious, dangerous, and repetitive tasks.

We build our systems entirely from scratch—engineering the hardware, firmware, low‑level controllers, simulators, and end‑user software in house. We are looking for driven researchers and engineers ready to embark on this journey with us and make a tangible, lasting impact.

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. In this role, you will design computationally efficient, real‑time algorithms that enable Friday to safely navigate dynamic, complex environments while executing dexterous manipulation tasks.

• Design and implement real‑time, kinematically feasible motion planning algorithms for Friday.
• Develop trajectory optimization and predictive control frameworks (e.g., Model Predictive Control) that ensure dynamic balance under high payloads, while respecting environmental and kinematic constraints in real time.
• Create robust pipelines for dynamic collision avoidance, integrating real‑time perception data to continuously update environment maps and re‑plan trajectories on the fly.
• Formulate algorithms for coordination between mobile base navigation and upper‑body bimanual manipulation, ensuring smooth and safe whole‑body coordination.
• Validate planning frameworks within our in‑house simulator and deploy them on physical robot hardware.
• Collaborate closely with the perception, control, and machine learning teams to integrate multi‑modal sensor inputs (e.g., vision, tactile) into the planning loop, enabling robust, end‑to‑end task execution.
• Collaborate with hardware and firmware teams to understand physical constraints—including actuator limits and communication latencies—ensuring planned trajectories are physically feasible on the hardware.

• MS, or Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a strictly 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—encompassing both custom‑built and commercially available systems.
• Deep theoretical and practical understanding of classic and modern planning algorithms (e.g., GCS, RRT*, PRM) alongside trajectory optimization (e.g., Traj Opt) and predictive control techniques (e.g., MPPI).
• Strong background in optimization theory and state estimation, with a deep commitment to mathematical exactness for 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 applied to 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.