Machine Learning / MLOps Engineer

Machine Learning / MLOps Engineer

We - as Cloudtech Consulting are looking for a skilled ML Engineer for our client:

Omniaz – the AI-first company behind OmniShelf

A little about themselves:

At Omniaz, we're building OmniShelf – a cutting-edge AI and Computer Vision platform that brings intelligence to physical retail shelves. Our system automatically detects and identifies products, tracks shelf availability, and verifies planogram compliance and provides recommendations. We are the only solution that works 100% offline to capture shelf data, process and analyze it, and execute store tasks, directly on the Edge.

We’re not here to play catch-up. We’re here to lead.

You’ll be joining a dedicated R&D team working on deep learning models and ML systems – focused purely on research, prototyping, and taking Computer Vision models to production. We’re expanding, and looking for people who are problem solvers, love optimization, and live for the thrill of solving real-world AI challenges.

We’re looking for a Machine Learning / MLOps Engineer

Focus: Computer Vision, Python, scalable data pipelines.

Help us build and scale the future of AI in retail.

What You’ll Do

• Design, train, and deploy CV models (object detection, segmentation, classification etc.) in real-world retail environments
• Build robust ML pipelines for data ingestion, model training, evaluation, deployment, and monitoring
• Own and optimize production ML infrastructure
• Work closely with product team to turn prototypes into real features
• Push boundaries – suggest and experiment with new techniques, tools, and ideas

What We’re Looking For

• Strong background in Computer Science, Machine Learning, or similar
• Solid Python skills and experience with key libraries (PyTorch/TensorFlow, OpenCV)
• Experience in building production-ready ML systems and automating workflows (CI/CD for ML, Docker, etc.)
• Problem solver with strong debugging and optimization instincts
• Comfortable working independently in a fully remote team

Sounds like you?

Let’s build the future of retail AI – together.