Training and Quality Consultant

We are partnering with a prestigious investment bank to find a highly skilled and hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base.

The role is to define and set up a greenfield standardized MLOps framework for capital markets and set up all the tools and best practices to educate data scientists and equip them with the right tools and expertise. A strong understanding of DevOps, machine learning, and data engineering is required to enable the right candidate to implement the MLOps processes.

You will gain exposure to various business areas and stakeholders, so relationship building and good communication will be key. You will bring expertise in data science or data engineering, with a specific focus on MLOps for at least 2 years. This platform is critical and will be rolled out across the bank, so we are looking for only the highest calibre candidates with experience building and being responsible for greenfield MLOps pipelines that handle very large datasets.

You will be responsible for building out a greenfield standardized framework for capital markets. The core platform is built on Azure Databricks Lakehouse, consolidating data from various front and Middle Office systems to support BI, MI, and advanced AI/ML analytics.

As a lead, you will shape the MLOps framework and establish best practices for deploying and managing AI/ML solutions for a diverse and dynamic user base, including data scientists, quants, risk managers, traders, and other tech-savvy users.

• 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.).

Requirements:

• 2+ years of experience in MLOps and at least 3 years in AI/ML engineering.
• Proficiency with ML frameworks and libraries in Python.
• Expertise in Azure DevOps and GitHub Actions.
• Strong programming skills in Python and SQL; 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.

Work on a greenfield project with a major global investment bank. Play a key role in building scalable AI/ML solutions across Capital Markets. Remote work flexibility with a competitive day rate.

If you are a talented MLOps professional with the expertise to help build and scale advanced AI/ML solutions in the investment banking space, we would love to hear from you.