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 caliber 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 Data Ops, Dev Ops, Model Ops ,and LLMOps to standardize and accelerate the AI/ML lifecycle.
- Collaborate with Data Scientists teams across Front office Quant teams Sales/Trading desks to build monitor maintain AI ML solutions.
- Adopt cutting-edge advancements in GenAI LLM technologies to keep the platform at the forefront of innovation.
- Align with bank’s central Enterprise Advanced Analytics & Artificial Intelligence group ensure alignment organizational goals strategies governance.
- Manage large datasets support data preparation integration analytics across various data sources (orders quotes trades risk etc.).
Essential Requirements:
- 2+ years of experience in MLOps at least 3 years in AI ML engineering.
- Expertise in Azure Databricks associated services.
- Proficiency with ML frameworks libraries Python.
- Proven experience deploying maintaining LLM services solutions.
- Expertise in Azure Dev Ops Git Hub Actions.
- Familiarity with Databricks CLI Databricks Job Bundle.
- Strong programming skills Python SQL; familiarity Scala is plus.
- Solid understanding of AI ML algorithms model training evaluation (including hyperparameter tuning), deployment monitoring governance.
- Experience handling large datasets performing data preparation integration.
- Experience Agile methodologies SDLC practices.
- Strong problem-solving analytical communication skills.
Why Join Us?
Work on a greenfield project major global investment bank. Gain deep expertise MLOps Azure Databricks GenAI LLM technologies . Play key role building scalable A I ML solutions Capital Markets . Remote work flexibility competitive day rate .
If you are talented MLOps professional expertise help build scale advanced A I ML solutions investment banking space we’d love hear from you Apply now!
How to Apply:
If you meet qualifications excited about this opportunity please submit your CV We look forward hearing from you!