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

Apply Now

Machine Learning Engineer

Reed
Glasgow
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer - London

Machine Learning Engineer - AI and Automation

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

ML Ops Engineer

Remote (Occasional London Meetups) | Full-Time, Permanent | UK Based | Cannot sponsor


Specialising in Azure ML, Data Integration & Scalable ML Ops

Are you an experienced ML Ops Engineer with a passion for deploying scalable machine learning solutions in Azure? This remote-first role (with occasional meetups in London) offers the opportunity to work on impactful data analytics projects in the pensions advisory space.


About the Role

You’ll be part of a forward-thinking analytics team that supports over 1,400 pension schemes and delivers insights using advanced technology and data science. We value innovation, collaboration, and continuous learning.

Please note: We are unable to offer visa sponsorship for this role. Applicants must have the right to work in the UK.


Key Responsibilities

  • Azure ML Operations: Design, deploy, and manage ML models in production using Azure ML.
  • Data Integration: Build and maintain data pipelines using SQL and Azure Data Factory (ADF).
  • ML Ops: Implement CI/CD workflows, monitor model performance, and manage retraining pipelines.
  • Python Development: Write clean, scalable code and manage version control using Git.
  • Cross-functional Collaboration: Work closely with actuaries, analysts, and developers to translate data science into actionable insights.
  • Innovation & Support: Stay current with ML trends and support team learning in tools and techniques.


What You’ll Bring

Essential Experience:

  • Strong hands-on experience with Azure ML or Azure-based production environments.
  • Proficiency in Python, SQL, ADF (Azure Data Factory), and Git.
  • Solid understanding of ML Ops, CI/CD, and model lifecycle management.
  • Ability to communicate technical concepts to non-technical stakeholders.


Desirable:

  • Experience in pensions or regulated financial services.
  • Background in multidisciplinary team environments.

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.