Summary: The MLOps Engineer will support a major consumer goods firm in advancing their Data and AI initiatives by building and maintaining machine learning infrastructure. The role involves collaborating with Data Scientists and Platform Engineers to deploy AI solutions, optimize MLOps pipelines, and ensure the smooth operation of machine learning processes. The position requires hands-on experience with Azure Databricks and a strong understanding of various machine learning technologies. Occasional travel to West London is expected, while the primary work will be home-based.

Key Responsibilities:

• Build and maintain robust machine learning infrastructure for AI solutions.
• Identify and implement best practices for MLOps pipelines based on client needs.
• Gather requirements, manage model registration, and perform deployment tests.
• Collaborate with Data Scientists and Platform Engineers to roll out new features.
• Utilize infrastructure as code technology for MLOps and data solutions.
• Maintain understanding of Databricks and Azure ML.
• Propose and implement improvements for platform stability and efficiency.
• Ensure smooth day-to-day running of ML Ops and drive optimization.
• Share knowledge with the wider data community.

Key Skills:

• Proven experience deploying and managing ML models in Azure Databricks.
• Familiarity with Databricks, Unity Catalog, Python, Git, MLFlow, Delta tables, Azure DevOps.
• Hands-on development experience with Python, TensorFlow, PyTorch, scikit-learn, and the Python Data Science stack.
• Strong analytical and problem-solving skills with large-scale datasets.
• Experience in automation, CI/CD, and Agile development environments.
• Knowledge of monitoring for data drift and model performance.
• Experience with feature stores and event-driven applications.
• Ability to work independently and in a team, preferably in a consulting/IT services environment.

Salary (Rate): £550

City: London

Country: United Kingdom

Working Arrangements: hybrid

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT