Machine Learning Engineer – Perception Systems

About the role

We are seeking a Machine Learning Engineer to design and deploy advanced perception systems that interpret data from external sensors such as cameras and spatial sensing technologies. The role focuses on building intelligent, real‑time solutions that enable environmental awareness, object detection and situational understanding in dynamic environments.

Key responsibilities

• Develop and deploy machine‑learning models for real‑time perception using sensor data (cameras, radar‑like signals, or other spatial inputs).
• Build computer‑vision pipelines for object detection, tracking and scene understanding.
• Process large‑scale datasets to improve model accuracy, robustness and generalisation.
• Implement multi‑sensor data‑fusion techniques to enhance environmental understanding.
• Optimise models for low‑latency inference on edge or embedded hardware.
• Collaborate with hardware, software and data‑engineering teams.
• Continuously evaluate and improve model performance under diverse real‑world conditions.
• Stay up‑to‑date with advances in machine learning, perception and AI research.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics or a related field.
• 2–5 years of experience in machine learning, computer vision or related areas.
• Strong programming skills in Python and/or C++.
• Hands‑on experience with deep‑learning frameworks such as PyTorch or TensorFlow.
• Solid understanding of computer‑vision techniques (object detection, segmentation, tracking).
• Experience working with sensor‑generated or image‑based data.
• Strong foundation in linear algebra, probability and optimisation.

Required skills

• Python
• C++
• PyTorch
• TensorFlow
• Computer vision
• Sensor data processing & fusion
• Real‑time system optimisation