National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Engineer

In Technology Group
London
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer (SC Cleared)

Machine Learning Engineer | Cambridge | Consulting

Machine Learning Engineer

Machine Learning Engineer

Job Title: Machine Learning Engineer

Location: London (1 days per week onsite) – Flexible

Salary: £45,000 DOE + Benefits

Our Data Analytics business continues to grow and we are now looking for an experienced and technical Machine Learning (ML) Engineer to join one our offices with hybrid or remote UK working. This is an exciting role and would most likely suit someone with previous experience in a similar role where they have gained knowledge and experience of designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. You must have good technical knowledge of Phyton, SQL, CI/CD and familiar with Power BI.


A FTSE 250 company, they combine expertise and insight with advanced technology and analytics to address the needs of over 1,400 schemes and their sponsoring employers on an ongoing and project basis. We undertake administration for over one million members and provide advisory services to schemes and corporate sponsors in respect of schemes of all sizes, including 88 with assets over £1bn. We also provide wider ranging support to insurance companies in the life and bulk annuities sector.


The Team

The client is a specialist and multi-disciplinary team consisting of actuaries, data scientist and developers. Our role in this mission is to pioneer advancements in the field of pensions and beyond, leveraging state-of-the-art technology to extract valuable and timely insights from data. This enables the consultant to better advise Trustees and Corporate clients on a wide range of actuarial-related areas.


The Role

As a Machine Learning Engineer you will:


  • Model development. Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision-making processes, and improve client offerings.
  • Machine Learning Operations. Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scare data efficiently. Implement and maintain monitoring of model drifts, data-quality alerts, scheduled r-training pipelines.
  • Data Management and Preprocessing. Collect, clean and preprocess large datasets to facilitate analysis and model training. Implement data pipelines and ETL processes to ensure data availability and quality.
  • Software Development. Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review.
  • Work closely with actuarial analysts, actuarial modelling team (AMT) and other colleagues to integrate data science findings into practical advice and strategies.
  • Stay abreast of new trends and technologies in Data Science technologies and pensions to identify opportunities for innovation.
  • Provide training and support to other team members on using machine learning tools and understanding analytical techniques.
  • Interpret and explain machine learning concepts and findings to other members of the analytics team and non-technical stakeholders.


Your profile

Essential Criteria

  • Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments.
  • Experience in data wrangling using Python, SQL and ADF.
  • Experience in CI/CD and DevOps/MLOps and version control.
  • Familiarity with data visualization and reporting tools, ideally PowerBI.
  • Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders.
  • Experience in the pensions or similar regulated financial services industry is highly desirable.
  • Experience in working within a multidisciplinary team would be beneficial.



We offer an attractive reward package; typical benefits can include:

  • Competitive salary
  • Participation in annual discretionary Bonus Scheme
  • 25 days holiday plus flexibility to buy or sell holiday
  • Flexible Bank holidays
  • Pension scheme, matching contribution structure
  • Healthcare cash plan
  • Flexible Benefits Scheme to support you in and out of work, helping you look after you and your family covering Security & Protection, Health & Wellbeing, Lifestyle
  • Life Assurance cover, four times basic salary
  • Rewards (offers High Street discounts and savings from retailers and services providers as well as offers available via phone)
  • Employee Assistance Programme for you and your household
  • Access to a digital GP service
  • Paid volunteering day when participating in Company organised events
  • Staff referral scheme when you introduce a friend
National AI Awards 2025

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.

10 AI Recruitment Agencies in the UK You Should Know (2025 Job‑Seeker Guide)

Generative‑AI hype has translated into real hiring: Lightcast recorded +57 % year‑on‑year growth in UK adverts mentioning “machine learning”, “LLM” or “gen‑AI” during Q1 2025. Yet supply still lags. Roughly 18,000 core AI professionals work in the UK, but monthly live vacancies hover around 1,400–1,600. That mismatch makes specialist recruiters invaluable—opening stealth vacancies, advising on salary bands and fast‑tracking interview loops. But many tech agencies sprinkle “AI” on their website without an active desk. To save you time, we vetted 50 + consultancies and kept only those with: A registered UK head office (verified via Companies House). A named AI/Machine‑Learning or Data practice.

AI Jobs Skills Radar 2026: Emerging Frameworks, Languages & Tools to Learn Now

As the UK’s AI sector accelerates towards a £1 trillion tech economy, the job landscape is rapidly evolving. Whether you’re an aspiring AI engineer, a machine learning specialist, or a data-driven software developer, staying ahead of the curve means more than just brushing up on Python. You’ll need to master a new generation of frameworks, languages, and tools shaping the future of artificial intelligence. Welcome to the AI Jobs Skills Radar 2026—your definitive guide to the emerging AI tech stack that employers will be looking for in the next 12–24 months. Updated annually for accuracy and relevance, this guide breaks down the top tools, frameworks, platforms, and programming languages powering the UK’s most in-demand AI careers.

How to Find Hidden AI Jobs in the UK Using Professional Bodies like BCS, IET & the Turing Society

Stop Scrolling Job Boards and Start Tapping the Real AI Market Every week a new headline announces millions of pounds flowing into artificial-intelligence research, defence initiatives, or health-tech pilots. Read the news and you could be forgiven for thinking that AI vacancies must be everywhere—just grab your laptop, open LinkedIn, and pick a role. Yet anyone who has hunted seriously for an AI job in the United Kingdom knows the truth is messier. A large percentage of worthwhile AI positions—especially specialist or senior posts—never appear on public boards. They emerge inside university–industry consortia, defence labs, NHS data-science teams, climate-tech start-ups, and venture studios. Most are filled through referral or conversation long before a recruiter drafts a formal advert. If you wait for a vacancy link, you are already at the back of the queue. The surest way to beat that dynamic is to embed yourself in the professional bodies and grassroots communities where the work is conceived. The UK has a dense network of such organisations: the Chartered Institute for IT (BCS); the Institution of Engineering and Technology (IET) with its Artificial Intelligence Technical Network; the Alan Turing Institute and its student-driven Turing Society; the Royal Statistical Society (RSS); the Institution of Mechanical Engineers (IMechE) and its Mechatronics, Informatics & Control Group; public-funding engines like UK Research and Innovation (UKRI); and an ecosystem of Slack channels and Meetup groups that trade genuine, timely intel. This article is a practical, step-by-step guide to using those networks. You will learn: Why professional bodies matter more than algorithmic job boards Exactly which special-interest groups (SIGs) and technical networks to join How to turn CPD events into informal interviews How to monitor grant databases so you hear about posts months before they exist Concrete scripts, portfolio tactics, and outreach rhythms that convert visibility into offers Follow the playbook and you move from passive applicant to insider—the colleague who hears about a role before it is written down.