Machine Learning Engineer
Core
Formulate, train, and deploy machine learning models for robotic systems to perceive the world through vision and sensors, enabling reliable operation in industrial environments.
Role type
Machine Learning Engineer (Robotics)
Builds
Scalable robotics platforms with deep neural networks for perception, control, and real-time optimization.
Domain
Industrial robotics, computer vision, and mechatronics.
Deliverable
production ML models
Required skills
deep learning (computer vision), state-estimation, ML mathematics (probability, statistics, optimisation), Python, C++, PyTorch/TensorFlow/JAX, MLOps, distributed training (multi-GPU/cloud), modular software design, data pipeline engineering, evaluation and benchmarking frameworks, sensor integration, pose estimation, object detection/segmentation, camera calibration.
Preferred skills
GPU acceleration, model optimisation, Docker.
Technologies
PyTorch, TensorFlow, JAX, Python, C++, Docker, multi-GPU/cloud infrastructure.
Responsibilities
Develop and deploy robust deep neural networks for robotics including object detection, segmentation, and scene understanding; Build scalable pipelines for training, fine-tuning, inference, and real-time optimization; Develop and maintain data pipelines for collection, ingestion, curation, versioning, and synthetic data generation; Work with distributed training systems and integrate models into robotics pipelines.
Seniority
Mid-Senior, hands-on IC