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

Nominate & Attend

Machine Learning Engineer

City of London
1 week ago
Create job alert

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

In Technology Group Ltd is acting as an Employment Agency in relation to this vacancy

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer with Data Engineering expertise

Machine Learning Engineer with Data Engineering expertise

Machine Learning Engineer with Data Engineering expertise

Machine Learning Engineer with Data Engineering expertise

Machine Learning Engineer with Data Engineering expertise

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.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.