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We're building a Computer Vision Agentic Platform that automates the entire CV model lifecycle from data cleanup and model training to evaluation, deployment, and monitoring.
You'll join a small, autonomous team of 3–5 engineers (plus interns) working alongside dedicated AI/ML engineers and computer vision scientists at ST Engineering, AI.DA Strategic Technology Centre (STC). Your role is to act as the CV expert and also spin up MVPs using CV and Generative AI to validate ideas before we build at scale.
What You'll Build
MVPs & Proof-of-Concepts
What You Bring
Engineering & Product Building
• 4+ years of hands-on software engineering experience with a proven track record of shipping complete, user-facing applications from inception to production—not just APIs or microservices, but products people use
• Strong Python skills with production-grade API development (FastAPI, Flask, gRPC)
• Solid system design and architecture skills
• Experience with containerization (Docker, Kubernetes)
• CI/CD pipeline experience (GitHub Actions)
Computer Vision & ML
• Hands-on experience training, evaluating, and deploying CV models (classification, detection, segmentation)—you've done this yourself, not just built infra around it
• Practical understanding of data-quality pitfalls, augmentation strategies, and model evaluation methodology
• Familiarity with CV toolkits: PyTorch, OpenCV, or Ultralytics YOLO
• Experience with model serving and packaging (TorchServe, ONNX Runtime, or similar)
• Ability to build automated evaluation using pytest, MLflow, or Weights & Biases
• GPU infrastructure and compute environments - CUDA and cuDNN management, multi-GPUs training across Ubuntu server
What We Offer
• Hybrid work setup: 2–3 days in office per week
• Startup feel with enterprise resources—international team with backgrounds
• Low-bureaucracy, high-impact environment where your code directly powers next-gen AI deployment
• Direct collaboration with top AI researchers and computer vision scientists
• Culture of experimentation, self-development, and knowledge sharing
Job ID: 146448655