Role Summary

Join the autonomy-stack team to research, implement and harden state-of-the-art perception algorithms that let mobile robots see, understand and safely navigate challenging environments, from object detection and terrain mapping to docking-structure detection and anomaly alerts.

Environment: Mobile robots for warehouses, factories, green-houses.

Tech Stack: Python (model training) | C++ | Rust (deployment).

Collaboration: Navigation & Fleet-management teams | QA | Hardware.

Main Responsibilities

• Contribute to the implementation of various components of our robot perception system (e.g. object detection/tracking, terrain mapping, situation classification, structure detection during docking, and anomaly detection).
• Develop/improve the implementation of each step of our sensor data processing pipeline as well documented industry ready software modules and libraries - Currently we use Python (for neural network model training) and Rust/C++ (for deployment).
• Carry out QA of the perception algorithms on the robot during prerelease testing.
• Help build benchmarks to automatically test the performance of the perception system in a range of edge cases.
• Help build tools that allow us to monitor the performance of the perception system when deployed in the field.
• Provide support and issue triage for deployments of the robot.
• Carry out testing and characterization of cameras, laser scanners and other sensor devices.
• Work closely with other teams (e.g. navigation team and fleet management team) to ensure operational requirements are met.

Qualifications & Experience

• Bachelor's Degree in Information Technology or relevant fields.
• No experience required; open to fresh grads with mandatory exposure on robotics related projects.

Mandatory Technical (Essential):

• Strong Python for ML model training.
• Proficient C++ or Rust for real-time deployment.
• Hands-on with computer‑vision / perception algorithms.
• Experience designing sensor-data processing pipelines.

Tools & Methods (Required):

• Software-development lifecycle & design patterns.
• CI, DevOps and automated QA/benchmarking for perception systems.

Domain Knowledge (Highly Valued):

• Delivery of combined hardware/software products in real-world settings.
• Robotics sensors (cameras, LiDAR) calibration & testing.

Soft Skills (Important):

• Detail-oriented, committed to seeing algorithms run on real robots.
• Clear communicator and team collaborator.