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Our client builds an AI product for creative professionals, and machine learning is at the core of it. They need an MLOps Lead who connects the ML researcher...
MLOps Lead / ML Platform Engineer | Qbitech Responsibilities check_circle Take ownership of the ML infrastructure and the CI/CD pipelines, and keep improving them check_circle Watch the production systems, investigate incidents, and make alerting and automation better check_circle Control how models and ML features are released from one environment to the next check_circle Keep the code quality high, the systems reliable and the architecture ready to scale check_circle Create and support internal tools that make ML development faster check_circle Help with releases find the risks early and make delivery more efficient check_circle Look after the core infrastructure and the internal platforms that are already in place shield Requirements At least 5 years of work in MLOps, DevOps, backend engineering or a related field Very good Python Practical experience with CI/CD, Docker and a public cloud, ideally AWS Good knowledge of how ML models are developed, released and operated A strong problem solver with solid system design skills A plus: Kubernetes, PyTorch or TensorFlow, data pipelines, model versioning What will be your next steps? 01 chat_bubble Quick non-technical conversation Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making. 02 code 60 to 90 minutes technical interview This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client’s requirements. 03 groups Client interview In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team. 04 workspace_premium Offer Congratulations on successfully completing our evaluation process. We are pleased to extend an offer and recommend you to our clients. Fill in your details below. We'll get back to you shortly. 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