We are looking for a Senior Navigation Engineer to lead the design, development, and deployment of navigation and motion planning systems for our autonomous mobile robot (AMR) fleet operating in industrial and warehouse environments.

This is a hands-on, end-to-end role. You will own the full planner-to-execution pipelinefrom global path planning and local trajectory optimization to real-time controller execution on physical robots. The ideal candidate has deep experience not only designing planning algorithms, but also implementing controllers, tuning them on real hardware, and deploying systems in production environments.

Key Responsibilities :

Navigation & Motion Planning :

- Own the complete navigation pipeline, including global path planning, local trajectory generation, and real-time control execution

- Design, implement, and optimize motion planning algorithms such as A-, Hybrid A-, RRT/RRT-, PRM, lattice planners, and state lattice approaches for industrial environments

- Develop trajectory generation and smoothing techniques that produce dynamically feasible paths, respecting velocity, acceleration, and jerk constraints

- Evaluate and apply trade-offs between search-based and sampling-based planning methods for different operational scenarios

Controls & Execution :

- Implement and tune trajectory tracking controllers including MPC, Pure Pursuit, Stanley, LQR, and PID-based controllers

- Design controllers for both differential drive and Ackermann steering platforms

- Model robot kinematics and dynamics, and ensure controllers respect real-world constraints such as actuator saturation and motion limits

- Integrate planner outputs with low-level motor controllers, closing the loop from trajectory to hardware actuation

- Debug and resolve real-world navigation and control issues including tracking errors, oscillations, instability, and edge-case failures

ROS2 & System Integration :

- Lead integration with the ROS2 / Nav2 stack, including :

1. Behavior Trees

2. Costmap configuration and custom layers

3. Custom planner and controller plugins (e.g., nav2_planner, nav2_controller)

- Develop robust, performant C++ systems (C++14/17) with real-time and safety considerations

- Design clean interfaces between high-level autonomy software and low-level control systems

Fleet Management & Multi-Robot Systems :

- Design and implement fleet-level navigation solutions including :

1. Multi-robot coordination

2. Traffic and intersection management

3. Task allocation

4. Deadlock detection and resolution

- Optimize system behavior under resource contention and high robot density

Leadership & Ownership :

- Act as a technical owner for navigation and controls

- Mentor junior engineers and provide architectural guidance

- Lead debugging efforts during field deployments and production incidents

Required Qualifications :

Experience :

- 5+ years of hands-on experience in AMR, AGV, or autonomous vehicle navigation

- Proven experience deploying navigation and control systems on physical robots in production

- Demonstrated ability to build planners and controllers from scratch, not just configure off-the-shelf solutions

- Strong experience tuning controllers on real hardware in warehouse or industrial environments

Technical Skills - Motion Planning :

- Deep understanding and implementation experience with : A-, Hybrid A-, RRT/RRT-, PRM, lattice and state lattice planners

- Experience with trajectory optimization and smoothing techniques (splines, minimum jerk/snap)

- Strong grasp of planning trade-offs for constrained, dynamic environments

Technical Skills - Controls (Critical) :

- Hands-on experience with MPC and classical control techniques

- Strong understanding of control theory, stability, and gain tuning

- Experience implementing controllers under real-world physical constraints

- Ability to debug control loops interacting with motors and actuators

Software & Systems :

- Strong proficiency in modern C++ (C++14/17)

- Deep experience with ROS2, including lifecycle nodes, executors, and custom interfaces

- Solid understanding of the Nav2 architecture

- Experience with multi-robot or fleet management systems

Education :

- Bachelors degree in Robotics, Computer Science, Electrical Engineering, or related field

- Masters or PhD preferred, but exceptional practical experience is equally valued

Preferred Qualifications :

- Experience with localization and sensor fusion (AMCL, SLAM)

- Integration of perception or computer vision into planning

- Simulation experience using Gazebo, Isaac Sim, or similar tools

- Exposure to safety-certified or functionally safe robotic systems

- Prior experience mentoring or leading engineers

What We Evaluate in Interviews :

We look for candidates who can :

- Clearly explain a planner and controller theyve built end-to-end

- Walk through real hardware tuning of MPC or other controllers

- Discuss trade-offs between planning and control approaches for industrial environments

- Explain how planner outputs are translated into motor-level commands

- Share real examples of debugging navigation issues in production

- Describe fleet-level challenges theyve solved, including traffic and deadlock handling

Experience : 5 to 11 years

Locations : Pune