Description
Location: Remote (London City- UK based) Very flexible working arrangements
Rate: Up to £850 per day (Outside IR35)
Job Type: 12-Month Contract (with extensions)
Industry: Investment Banking/Finance Technology
About the Role:
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. 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. 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.
Core 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.).
Essential Requirements:
- 2+ years of experience in MLOps
and at least 3 years in AI/ML engineering.
- Expertise 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
*Strong problem-solving,* analytical,* *communication skills.*
Why Join Us?
Work on a greenfield project with a major global investment bank. Gain deep expertise in MLOps ,Azure Databricks ,GenAI ,LLM technologies . Play a key role in building scalable A I / ML solutions across Capital Markets . Remote work flexibility with competitive day rate.
If you are a talented MLOps professional who can help build & scale advanced A I / ML solutions within investment banking space , we'd love to hear from you . Apply now!
How to Apply:
If you meet qualifications & are excited about this opportunity , please submit your CV . We look forward hearing from you!