SAP Technical MLOps Engineering Lead 

Bulgaria, Burgas 

285282941

WHAT YOU’LL DO

As the Technical MLOps Engineering Lead, you will orchestrate a team of MLOps Engineers within our domain teams to enable and support MLOps activities. Your responsibilities include designing, implementing, and optimizing MLOps processes, ensuring seamless integration between data science and production environments. Additionally, you will adhere to security concepts and architecture best practices while driving the execution of processes according to industry standards. You will also evaluate and adopt emerging technologies to enhance MLOps capabilities and efficiency, staying up-to-date with industry trends and innovations, and assessing new solutions for their suitability in improving our MLOps workflows. A curious, agile, and can-do mindset will ensure you integrate seamlessly into our team dynamic.

WHAT YOU’LL BRING

• Master’s or Ph.D. in Computer Science, Machine Learning, or related field.
• Experience developing and deploying machine learning models in production environments.
• Excellent problem-solving skills, collaborative team spirit, and strong communication abilities.
• Solid understanding of AI/ML concepts, including MLOps, demonstrated through hands-on experience with tools like Kubeflow for effective orchestration and management of machine learning workflows.
• Proficiency in Azure Data Lake Storage (ADLS), Azure Databricks, and SAP Business Technology Platform (BTP) technology, including SAP AI Core.
• Hands-on experience with ML experiment tracking tools such as MLFlow or Weights & Biases, and knowledge of orchestration and workflow pipelines for MLOps (e.g., Metaflow).
• Fluency in Python, including libraries such as Numpy, Pandas, Keras, scikit-learn, TensorFlow, and PyTorch, with demonstrated experience in Python backend development (e.g., FastAPI, Postgres, OpenAPI).
• Proven expertise in DevOps best practices, including version control, testing, deployment, and monitoring for machine learning models in production, with experience implementing Git-based version control systems and CI/CD pipelines using tools like Jenkins and GitHub.
• Proficiency in Infrastructure as Code (IaC) tools such as Terraform, enabling efficient management and automation of infrastructure provisioning and configuration.

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