Machine Learning Operations Engineer

Proactive.IT Appointments
London
1 week ago
Create job alert

11328SR5
£40k – 60k per year


Machine Learning Operations Engineer


Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have the following essential skills & experience:

Key Skills & Experience

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 in the company 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 within the company.

Technical Skills required

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

Benefits

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


Competitive salary
Participation in Discretionary Bonus Scheme
A set of core benefits including Pension Plan, Life Assurance cover and employee assistance programme, 25 days holiday and access to a qualified, practising GP 24 hours a day/365 days a year
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

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted. 


Proactive Appointments Limited operates as an employment agency and employment business and is an equal opportunities organisation

Related Jobs

View all jobs

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

Machine Learning Operations Engineer

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 Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.