Machine Learning Operations Lead

Machine Learning Operations Lead

Department: [SBL] Data Engineering

Employment Type:

Permanent – Full Time

Location:

Bristol

Compensation:
Competitive Package

The Machine Learning Operations Lead will be responsible for overseeing the development and deployment of the ML Ops platform for Project Pegasus. This role involves leading a cross‑functional team to ensure the successful implementation and integration of ML models into the live pricing environment. The ML Ops Lead will work closely with data scientists, data engineers, and external consultants to deliver a robust and scalable ML platform.

• Lead the development and deployment of the ML Ops platform.
• Oversee the design, build, and testing of API services in the development environment.
• Ensure the platform supports offline analytics, ML models, lookup tables, and pricing actions.
• Collaborate with cross‑functional teams to deliver the platform in an agile manner.
• Provide guidance on the implementation and management of Azure Cache (Redis), Postgres, Azure Redis, Databricks Delta Live tables, and Snowflake.
• Ensure the platform supports microservices and API‑driven architecture with sub‑2‑second calls.
• Develop and maintain documentation, architecture diagrams, and other technical artifacts.
• Manage the integration of the platform with RADAR and other systems.
• Ensure code is production ready and follows the SDLC best practices.

• Proven experience in ML Ops engineering, with a focus on Azure and Databricks.
• Strong knowledge of Postgres, Azure Cache (Redis) and Azure Redis.
• Experience with Databricks Delta Live tables and Snowflake.
• Experience with Docker and Azure Container Services.
• Familiarity with API service development and orchestration.
• Experience in Data (Delta) Lake Architecture (Azure).
• Excellent problem‑solving skills and ability to work in a collaborative environment.
• Strong communication skills and ability to work with cross‑functional teams.
• Experience with Azure Functions/Containers and Insights.
• Knowledge of integrating the platform with Snowflake for data storage and retrieval.
• Experience in managing the Software Development Life Cycle.
• Conducting peer reviews and pair programming.

• 25 days annual leave, rising to 27 days over 2 years’ service and 30 days after 5 years’ service. Plus bank holidays!
• Discretionary annual bonus
• Pension scheme – 5% employee, 6% employer
• Flexible working – we will always consider applications for those who require less than the advertised hours
• Flexi‑time
• Healthcare Cash Plan – claim cashback on a variety of everyday healthcare costs
• Electric vehicle – salary sacrifice scheme
• 100’s of exclusive retailer discounts
• Professional wellbeing, health & fitness app – Wrkit
• Enhanced parental leave, including time off for IVF appointments
• Religious bank holidays – if you don’t celebrate Christmas and Easter, you can use these annual leave days on other occasions throughout the year.
• Life Assurance – 4 times your salary
• 25% Car Insurance Discount
• 20% Travel Insurance Discount
• Cycle to Work Scheme
• Employee Referral Scheme
• Community support day

Somerset Bridge Group

• Industry
• Machine Learning
• NLP
• United Kingdom

Senior (5+ years of experience)