Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Operations Engineer

NLP PEOPLE
Newcastle upon Tyne
4 days ago
Create job alert

Machine Learning Operations Engineer


Department: [SBL] Data Engineering


Employment Type: Permanent – Full Time


Location: Newcastle


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.


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 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.

Benefits

  • 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

Company

Somerset Bridge Group


Experience Level

Senior (5+ years of experience)


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

2026 Machine Learning Operations (ML Ops) Graduate

Backend Machine Learning Engineer in London - Treefera

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.