About the Role

Gamasome is looking for a mid-level Autonomy Engineer to build and test the autonomy stack for an autonomous mobile robot (AMR), end to end — from sensor fusion and localisation through motion planning and control. This is a hands-on, from-the-ground-up robotics role: you'll be integrating open-source libraries directly and writing performance-critical code, not just configuring an existing framework. Responsibilities

Design and implement state estimation / sensor fusion pipelines (EKF/UKF) combining wheel odometry and IMU data, including filter tuning and consistency checks

Build and maintain SLAM & mapping capability — LiDAR SLAM, occupancy grids, loop closure

Implement localisation against a prior map using scan matching techniques (ICP/NDT/AMCL-style) at high pose rates

Develop layered costmaps (static/agile/inflation) from LiDAR and depth sensor input

Own motion planning across global (A*/D*) and local layers, including trajectory optimization and MPC

Implement control for trajectory tracking and safe motion on a differential-drive platform (stopping distances, safety zones, E-Stop handling)

Write and maintain sensor drivers / HAL wrappers for safety LiDAR, IMU, depth cameras, wheel encoders, and motor/drive controllers over fieldbus protocols (Modbus/CAN)

Handle sensor calibration, extrinsics, and time synchronization across the robot's sensor rig

Develop and validate in simulation first (Isaac Sim / MuJoCo) before sim-to-real transfer

Run rigorous validation — trajectory error (ATE/RPE), drift, latency/jitter,



and filter consistency checks

Maintain reliability discipline: reproducible tests, long-duration/soak testing, regression catching, and CI integration

Write clean, production-grade C++ and Python code following high engineering standards (e.g., Google style guides), using CMake, Cython, Docker, Git, and CI pipelines

Work with pub/sub middleware and protobuf (Zenoh, DDS, or similar) across multi-process node systems

Use logging and replay tools (e.g., MCAP) for debugging and evaluation. Requirements

Strong C++ and Python skills, including C/C++ for performance-critical code

Experience building autonomy stacks from the ground up — not solely reliant on ROS — with direct integration of open-source libraries

Real-time / performance engineering experience, meeting rate and latency targets on constrained compute

Solid foundation in linear algebra, estimation/probability, optimization, geometry & transforms, and differential-drive kinematics

Demonstrated experience across state estimation, SLAM, localisation, costmaps, motion planning, and control

Hands-on experience with sensor drivers/HAL layers and hardware calibration

Experience with simulation-first development and rigorous validation practices

Strong software engineering fundamentals — clean code, version control, CI/CD Nice to Have

Prior experience in the warehouse AMR/AGV domain Compensation will be competitive and in line with industry standards, based on the candidate's experience and expertise.

📌 AMR Autonomy Engineer (Mid-Level) (Bengaluru)
🏢 GAMASOME
📍 Bengaluru