Machine Learning Operations Engineer

Somerset Bridge; Bristol; Hybrid; GBP 125,000 - 150,000; Full time

Job summary

A technology firm in Bristol is seeking a Machine Learning Operations Engineer to support the development and maintenance of the ML Ops platform. This role involves building and maintaining data infrastructure, developing API services, and integrating ML models into the live environment. Ideal candidates should have strong experience in ML Ops engineering, particularly with Azure and Databricks, and possess excellent problem-solving and communication skills. This position offers hybrid working options and a range of benefits including annual leave and a pension scheme.

Benefits

25 days annual leave

Discretionary annual bonus

Pension scheme

Healthcare Cash Plan

Employee Referral Scheme

Qualifications

• Experience in ML Ops engineering, with a focus on Azure and Databricks.
• Familiarity with API service development and orchestration.
• Experience in Software Development Life Cycle.

Responsibilities

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

Skills

Experience in ML Ops engineering

Knowledge of Postgres

Experience with Docker

Strong problem-solving skills

Good communication skills

Tools

Azure

Databricks

Snowflake

Job 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.

Responsibilities:

• 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.

Requirements:

• 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 collaboratively.
• 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.

Additional Benefits:

• Hybrid working: 2 days in the office and 3 days remote.
• 25 days annual leave, increasing to 27 days after 2 years, and 30 days after 5 years, plus bank holidays.
• Discretionary annual bonus.
• Pension scheme: 5% employee, 6% employer.
• Flexible working options and flexi-time.
• Healthcare Cash Plan for healthcare costs.
• Electric vehicle salary sacrifice scheme.
• Exclusive retailer discounts.
• Wellbeing, health & fitness app - Wrkit.
• Enhanced parental leave, including IVF support.
• Religious bank holidays for flexible use.
• Life Assurance: 4x salary.
• Car and Travel Insurance discounts.
• Cycle to Work Scheme.
• Employee Referral Scheme.
• Community support day.