Locomotion & Controls Engineer

Innefu Labs Limited; Delhi; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Innefu Labs Limited is seeking a robotics researcher to design and train gait controllers for legged locomotion. You will develop simulation environments, create gait strategies, and transfer tested controllers to real robots, ensuring robust field performance.

The role requires 3–8 years of experience, MTech/PhD in robotics or controls, and hands-on work with simulators such as Isaac Sim, MuJoCo, or PyBullet. Strong C++/Python skills and state estimation expertise are essential.

Qualifications

• Proficiency in C++ and Python for robotics software development.
• Experience with state estimation using IMU and joint sensors.
• Familiarity with RL, MPC, or whole-body control for legged locomotion.
• Hands-on with at least one physics simulator (e.g., Isaac Sim, MuJoCo, PyBullet, Gazebo).
• Background in transferring controllers from simulation to real robots.

Responsibilities

• Build a simulation environment with randomized rough terrain.
• Develop gaits (walk, trot, stairs, crawl) using RL, MPC, or both.
• Transfer controllers from simulation to real robot and tune them in field tests.
• Write state estimation (body pose and velocity) from sensor data.
• Specify actuator and leg requirements to select suitable suppliers.

Skills

C++

Python

Reinforcement learning

Model predictive control

State estimation

Education

MTech/PhD in robotics or control systems

BTech/MTech/PhD in mechanical/electrical/aerospace/robotics

Tools

Isaac Sim

MuJoCo

PyBullet

Gazebo

RaiSim

legged_gym

OCS2

Pinocchio

Drake

Crocoddyl

Job description

Founded in 2010, Innefu Labs is anAI-driven R&D organisation focused on advanced Data Analytics andInformation Security solutions. With a strong emphasis on innovation andproduct engineering, the company develops globally competitive solutions addressingcomplex challenges in national security, cyber intelligence, and dataanalytics.

With 100+ successful deployments across theIndian Subcontinent, the Middle East, and Southeast Asia, Innefu hasestablished a strong presence in AI for National and Cyber Security. Itsproprietary products serve Defence and Intelligence agencies, Law Enforcementorganisations, Financial Intelligence Units, BFSI institutions, and Fortune 500companies.

Innefu specialises in building secure,high-performance products for sensitive and mission-critical environments, witha strong focus on innovation, reliability, scalability, and customersatisfaction

RoleOverview

Makes the robot walk, climb and recoveron mud, rock, snow and stairs — designing and training the gait controller insimulation and transferring it to the real robot.

Experience

3–8 years,

Education

MTech/PhDwith a thesis on legged locomotion. BTech/MTech/PhD in Mechanical, Electrical,Aerospace, Robotics or Control Systems. Very few people in India have builtlegged robots, so a strong humanoid, exoskeleton or legged-research backgroundalso counts.

Responsibilities

• Build the simulationenvironment with randomised rough terrain.
• Develop gaits (walk, trot,stairs, crawl) using reinforcement learning, model predictive control (MPC), orboth.
• Transfer controllers fromsimulation to the real robot (sim-to-real) and tune them in field tests.
• Write state estimation (bodypose and velocity) from IMU and joint sensors.
• Specify actuator and legrequirements to choose the off-the-shelf supplier.

Musthave

• C++ and Python.
• Rigid-body dynamics and controltheory: MPC, whole-body control, or RL for locomotion (PPO).
• At least one physics simulator:Isaac Sim / Isaac Lab, MuJoCo, PyBullet, Gazebo or RaiSim.
• Has run a controller on realrobot hardware, not only in simulation.

Goodto have

• Hands-on with commercialquadrupeds (Unitree, ANYmal, Spot, Deep Robotics) or their SDKs.
• Open-source legged stacks:legged_gym, OCS2, Pinocchio, Drake, Crocoddyl.
• Publications at ICRA, IROS,CoRL, RSS or Humanoids.
• Kalman filters / stateestimation; terrain-aware foothold planning.

Requirements

Responsibilities

• Build the simulationenvironment with randomised rough terrain.
• Develop gaits (walk, trot,stairs, crawl) using reinforcement learning, model predictive control (MPC), orboth.
• Transfer controllers fromsimulation to the real robot (sim-to-real) and tune them in field tests.
• Write state estimation (bodypose and velocity) from IMU and joint sensors.
• Specify actuator and legrequirements to choose the off-the-shelf supplier.

Musthave

• C++ and Python.
• Rigid-body dynamics and controltheory: MPC, whole-body control, or RL for locomotion (PPO).
• At least one physics simulator:Isaac Sim / Isaac Lab, MuJoCo, PyBullet, Gazebo or RaiSim.
• Has run a controller on realrobot hardware, not only in simulation.

Goodto have

• Hands-on with commercialquadrupeds (Unitree, ANYmal, Spot, Deep Robotics) or their SDKs.
• Open-source legged stacks:legged_gym, OCS2, Pinocchio, Drake, Crocoddyl.
• Publications at ICRA, IROS,CoRL, RSS or Humanoids.
• Kalman filters / stateestimation; terrain-aware foothold planning.