Locomotion And Controls Engineer

Innefu Labs; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Innefu Labs is seeking an experienced Locomotion & Controls Engineer in India to design and train gait controllers for legged robots, bridging simulation and real-world deployment. You will build robust simulators, implement efficient gaits, and optimize state estimation from sensor data.

The role requires 3–8 years in robotics locomotion, with advanced degrees in mechanical, electrical, aerospace, robotics, or control systems. Strong hands-on with simulators and real hardware is essential.

Qualifications

• 3–8 years of experience in locomo­tion & controls for legged robots.

Responsibilities

• Build the simulation environment with randomised rough terrain.
• Develop gaits (walk, trot, stairs, crawl) using reinforcement learning, MPC, or both.
• Transfer controllers from simulation to the real robot (sim-to-real) and tune in field tests.
• Write state estimation (body pose and velocity) from IMU and joint sensors.
• Specify actuator and leg requirements to choose off-the-shelf suppliers.

Skills

C++

Python

Reinforcement Learning

MPC

Robot simulation

Education

MTech/PhD with legged locomotion

BTech/MTech/PhD Mechanical/Electrical/Robotics/Control

Tools

Isaac Sim

MuJoCo

PyBullet

Gazebo

RaiSim

Job description

Job Description:

JD Locomotion &Controls Engineer

About Innefu Labs

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.
• PyTorch, GPU training, domainrandomisation.

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.
• PyTorch, GPU training, domainrandomisation.