Machine Learning & Computer Vision Engineer

Were hiring someone with real computer vision experience detection, segmentation, tracking, pose who can run experiments end to end and ship models into working systems.

Full-time or long-term contract (3–6 months).

What you’ll work on

• Image and video understanding
• Object detection, segmentation, keypoint detection, pose estimation, and tracking
• Temporal analysis of actions and multi-step processes
• Multimodal learning using visual, sensor, and time-series data
• Failure detection, confidence estimation, and automated verification
• Data collection, annotation, training, and evaluation pipelines
• Integrating trained models into larger software systems

You’ll review research, set baselines, compare model families, dig into failures, and recommend the practical path.

What we’re looking for

• Strong Python and PyTorch
• Solid modern computer vision and deep-learning architecture chops
• Hands-on work with image or video datasets
• Experience in detection, segmentation, tracking, pose estimation, or action recognition
• Designing controlled experiments and meaningful metrics
• Linux and GPU-based training
• Reading papers and turning them into working experiments
• Comfort with data collection, labelling, train/val, and model integration

Good to have

• Detection & segmentation: YOLO, RT-DETR, Mask R-CNN
• Pose & tracking: ViTPose, Keypoint R-CNN, ByteTrack
• Video / temporal: VideoMAE, Video Swin, MS-TCN
• Learning-based control: Behaviour Cloning, ACT, Diffusion Policy
• Multimodal learning, synthetic data, domain adaptation, uncertainty, or robotics apps

Who fits

Someone who owns an experimentation track — problem, data, models, comparison, clear recommendation. We want help deciding what to build, what to test, and how to prove it works.