Principal Computer Vision Scientist

Senior technical leader for our Computer Vision and AI/ML work. You'll own model architecture and experimentation through to production, and set the standards the team builds against. PhD-level role spanning research, engineering, and production systems.

What you'll do

• Lead research, design, and delivery of CV and AI/ML solutions
• Define model architecture, experiment strategy, validation methodology, and production-readiness criteria
• Train, fine-tune, and deploy models for object detection, segmentation, classification, OCR, feature matching, and visual search
• Own the full model lifecycle: dataset quality, annotation, training, evaluation, deployment, monitoring
• Build prototypes and PoCs; analyze failure cases and drive improvements
• Review and improve CV pipelines for latency, scalability, and reliability
• Set standards for evaluation, versioning, dataset management, and MLOps; mentor engineers

What you'll need

• PhD in CS, Computer Vision, ML, AI, Applied Math, EE, Robotics, or related field
• 7+ years hands-on ML/deep learning with a strong CV focus
• Strong Python; PyTorch and/or TensorFlow; OpenCV, NumPy, Pandas, scikit-learn
• Solid grasp of classical CV and modern architectures (CNNs, ViT, YOLO, Mask R-CNN, CLIP/SAM-like)
• Proven experience taking models to production and optimizing for latency, memory, and scale
• REST APIs, Docker, CI/CD, model versioning, experiment tracking, MLOps
• Strong data/annotation/error-analysis discipline; Agile; ownership mindset

Nice to have
Edge/mobile inference (ONNX, TensorRT, OpenVINO, TFLite, CoreML) · large-scale image pipelines · synthetic data, active learning, weak supervision · multimodal/vision-language models · cloud ML platforms · publications or patents