Robotics / Computer Vision Engineer

As a Robotics / Computer Engineer, you will be responsible for designing and implementing the perception systems that make adaptable robotics possible. You'll develop the perception stack that transforms raw sensor data into precise, sub-millimeter accurate geometry-key to enabling collision-free planning and navigation.

This is a handson role: you'll select and evaluate sensors, build calibration tools, implement 3D pipelines, and ensure system robustness for deployment in industrial environments. Your work will directly influence downstream planning, learning, and control systems.

What you'll do:

• Evaluate and integrate various sensors, experimenting with hardware setups and assessing their data quality based on mounting and environmental constraints.

• Develop calibration routines for intrinsic/extrinsic parameters, build tooling to validate and correct drift, and ensure frame accuracy.

• Perform image registration: aligning RGB-D, point clouds, and geometries to CAD models using techniques like feature extraction, RANSAC, ICP, and outlier handling.

• Ensure perception data feeds accurately into digital twin simulations and machine learning pipelines.

• Build robust logging, replay, health checks, and failure detection systems for reliable deployment.

• At least 3 years of experience shipping real-world computer vision and 3D systems beyond prototypes, especially in robotics, inspection, or metrology.

• Hands-on experience with depth sensing technologies (stereo, RGB-D, ToF, structured light, laser profiling) and understanding of their real-world tradeoffs.

• Strong fundamentals in geometry: coordinate frames, transforms, rotations, quaternions, and geometric error handling.

• Expertise in registration techniques-feature-based, ICP-style alignment, outlier rejection-and calibration/validation tooling.

• Proficiency in programming within a team environment.

• Ability to troubleshoot challenging real-world conditions like reflective surfaces, lighting variations, partial occlusions, or environmental noise.

• Clear communicator, a team player, with a methodical approach to testing assumptions.

Nice-to-have skills:

• Experience working in harsh industrial environments like welding or heavy industry.

• Exposure to robotics integration, including robot frames, tooling, latency constraints, and ROS2/MoveIt.

• Knowledge of edge deployment with GPUs, TensorRT, CUDA, and reliability monitoring.

• Experience with simulation tools like Isaac Sim or synthetic data generation.

• Interest in reinforcement learning pipelines.

• Generous Salary Package