Machine Learning Operations Engineer

Somerset Bridge; Bristol; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A leading company in the UK is seeking a Machine Learning Operations Engineer to develop and maintain the ML Ops platform. The role involves creating data infrastructure, API services, and integrating ML models while collaborating with cross-functional teams. Offering hybrid working and extensive benefits including healthcare cash plans and flexible working options.

Benefits

Hybrid working

25 days annual leave, increasing with service

Discretionary annual bonus

Pension scheme

Healthcare Cash Plan

Electric vehicle salary sacrifice scheme

Enhanced parental leave

Life Assurance

Qualifications

• Experience in ML Ops engineering with a focus on Azure and Databricks.
• Strong knowledge of Docker and API service development.
• Experience with Data (Delta) Lake Architecture.

Responsibilities

• Develop API services using Databricks and Azure.
• Integrate platform with Snowflake for data storage.
• Conduct load, end-to-end, and performance testing.

Skills

Problem-solving

Collaboration

Communication

Tools

Azure

Databricks

Docker

Postgres

Snowflake

Job description

Machine Learning Operations Engineer

Department: [SBL] Data Engineering

Employment Type: Permanent - Full Time

Location: Bristol

Compensation: Competitive Package

Description

The Machine Learning Operations Engineer will support the development and maintenance of the ML Ops platform for Project Pegasus. This role involves building and maintaining the data infrastructure required for the platform, developing API services, and ensuring the integration of ML models into the live environment.

What you'll be responsible for:

• Develop and maintain API services using Databricks and Azure.
• Implement and manage Azure Cache (Redis) and Azure Redis.
• Utilize Databricks Delta Live tables for data processing and analytics.
• Integrate the platform with Snowflake for data storage and retrieval.
• Collaborate with cross-functional teams to deliver the platform in an agile manner.
• Ensure the platform supports offline analytics, ML models, lookup tables, and pricing actions.
• Conduct load, end-to-end, and performance testing.
• Produce pipeline code for running ML Ops jobs and create an Azure DevOps (GitHub) process for source control and deployment.

What you'll need:

• Experience in ML Ops engineering, with a focus on Azure and Databricks.
• Knowledge of Postgres, Azure Cache (Redis) and Azure Redis.
• Experience with Databricks Delta Live tables and Snowflake.
• Experience in Data (Delta) Lake Architecture.
• Experience with Docker and Azure Container Services.
• Familiarity with API service development and orchestration.
• Strong problem-solving skills and ability to work in a collaborative environment.
• Good communication skills and ability to work with cross-functional teams.
• Experience with Azure Functions/Containers and Insights (not essential)
• Experience in Software Development Life Cycle.

Our Benefits

• Hybrid working – 2 days in the office and 3 days working from home
• 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