Senior Research Scientist: Planning and Control

Holiday Robotics Inc.; Mountain View (CA); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

Equity packages

Relocation stipend

Job summary

Holiday Robotics Inc. in Mountain View, California is searching for a Senior Research Scientist specialized in planning and control. You'll drive the development of sophisticated motion planning and control algorithms for our humanoid robot, enabling safe and efficient navigation in complex environments.

The ideal candidate will possess a strong research background and a minimum of 7 years' experience in robotics, with expertise in motion planning and sophisticated control methods. A competitive salary range of $200,000 - $250,000 is offered, along with comprehensive health benefits and relocation assistance.

Qualifications

• 7+ years of experience in robotics focusing on motion planning and control.
• Deep understanding of motion planning algorithms and trajectory optimization.
• Proficiency in coding with AI-assisted tools.

Responsibilities

• Develop motion planning, trajectory optimization, and navigation algorithms.
• Implement real-time algorithms for safe navigation and manipulation.
• Work closely with cross-functional teams to deploy algorithms on hardware.

Skills

Motion planning

Trajectory optimization

Control algorithms

Artificial Intelligence coding

Education

MS or Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science

Job description

Senior Research Scientist: Planning and Control

About the Role

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.

Key Areas

Required Qualifications

• 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., TrajOpt), 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.

Preferred Qualifications

• 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.

What We Offer

• 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.