Summary: The Machine Learning Operations (MLOps) Lead role at a prestigious investment bank involves establishing a greenfield framework for deploying and managing scalable AI/ML solutions tailored for the front and middle office. The position requires hands-on expertise in MLOps, data engineering, and DevOps, with a focus on building AI/ML CI/CD pipelines on Azure Databricks. The lead will collaborate with various teams to implement best practices and ensure alignment with organizational goals while managing large datasets. This role offers significant exposure to different business areas and stakeholders within the bank.

Key Responsibilities:

• Lead the development of AI/ML CI/CD pipelines and frameworks for supporting AI/ML and Data Science solutions on Azure Databricks.
• Define and implement best practices for DataOps, DevOps, ModelOps, and LLMOps to standardize and accelerate the AI/ML life cycle.
• Collaborate with Data Scientists and teams across Front Office Quant teams, Sales/Trading desks to build, monitor, and maintain AI/ML solutions.
• Adopt cutting-edge advancements in GenAI and LLM technologies to keep the platform at the forefront of innovation.
• Align with the bank's central Enterprise Advanced Analytics & Artificial Intelligence group to ensure alignment with organizational goals, strategies, and governance.
• Manage large datasets and support data preparation, integration, and analytics across various data sources (orders, quotes, trades, risk, etc.).

Key Skills:

• 2+ years of experience in MLOps and at least 3 years in AI/ML engineering.
• Knowledge in Azure Databricks and associated services.
• Proficiency with ML frameworks and libraries in Python.
• Proven experience deploying and maintaining LLM services and solutions.
• Expertise in Azure DevOps and GitHub Actions.
• Familiarity with Databricks CLI and Databricks Job Bundle.
• Strong programming skills in Python and SQL; familiarity with Scala is a plus.
• Solid understanding of AI/ML algorithms, model training, evaluation (including hyperparameter tuning), deployment, monitoring, and governance.
• Experience in handling large datasets and performing data preparation and integration.
• Experience with Agile methodologies and SDLC practices.
• Strong problem-solving, analytical, and communication skills.

Salary (Rate): £850

City: London City

Country: United Kingdom

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: Senior

Industry: Finance