Robotic Algorithm Engineer Job at Scylla Solutions LLC, Milpitas, CA

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  • Scylla Solutions LLC
  • Milpitas, CA

Job Description

We are building a next-generation humanoid robot platform with high-bandwidth torque-controlled joints and full-body actuation. Our short- to mid-term goal is to achieve robust and reliable locomotion in indoor service and industrial environments.

As a Robotics Algorithm Engineer focused on Locomotion, you will work across simulation, learning-based control, state estimation, and real-robot deployment. This is a highly hands-on role requiring both strong implementation skills and the ability to debug complex real-world robotic behaviors.

We are looking for engineers who not only implement algorithms, but also develop their own technical insights and adapt quickly in a rapidly evolving robotics landscape.

Responsibilities

Locomotion & Learning-Based Control

  • Develop and deploy RL-based locomotion policies for humanoid robots
  • Design training pipelines including domain randomization and sim-to-real transfer
  • Improve policy robustness for indoor service and industrial use cases
  • Analyze and debug failure modes from both simulation and real-world testing

Full-Body Control & Modeling

  • Work on whole-body control frameworks integrating learned policies
  • Understand and leverage robot dynamics models for stability and contact reasoning
  • Contribute to state estimation using IMU, joint encoders, and contact sensing

Simulation & Tooling

  • Build and maintain locomotion simulation environments (Mujoco / Isaac)
  • Design training environments and reward shaping strategies
  • Analyze the simulation-real gap and iterate on mitigation strategies

Real Robot Deployment

  • Deploy policies to hardware with torque-controlled, high-bandwidth actuators
  • Perform real-robot tuning, debugging, and performance optimization
  • Work closely with firmware, motor control, and hardware teams

Qualifications

Must Have

  • 3+ years of experience in robotics, control, or locomotion-related roles
  • Strong C++ and Python programming skills
  • Experience applying reinforcement learning to robotics control problems
  • Experience deploying algorithms on real robots (not simulation-only)
  • Solid understanding of rigid body dynamics and feedback control
  • Familiarity with state estimation for legged robots
  • Experience working in Linux environments

Nice to Have

  • Experience with humanoid or legged robots
  • Whole-Body Control or MPC exposure
  • Mujoco / Isaac Gym / Isaac Sim experience
  • Experience addressing sim-to-real transfer challenges
  • Familiarity with Pinocchio, CasADi, or similar tools
  • CUDA or large-scale RL training experience
  • ROS2 experience

Work Mode

  • On-site required
  • Up to 10% of travel

Job Tags

Temporary work

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