MLOps Engineer

MLOps Engineer

Full-Time 55000 - 65000 £ / year (est.) No working from home possible
XPS Group

At a Glance

  • Tasks: Develop and optimise machine learning models using Azure ML in a collaborative environment.
  • Company: Join XPS Group, a leading consultancy in pensions and insurance with a vibrant culture.
  • Benefits: Enjoy competitive salary, flexible holidays, healthcare plans, and volunteer opportunities.
  • Other info: Be part of a diverse team with excellent career growth and training opportunities.
  • Why this job: Make a real impact in the pensions sector while working with cutting-edge technology.
  • Qualifications: Experience in MLOps, Python, SQL, and CI/CD practices is essential.

The predicted salary is between 55000 - 65000 £ per year.

About XPS Group: XPS Group is a prominent and growing UK consultancy and administration firm within the pensions and insurance sectors. As a FTSE 250 company with over 2000 employees, we leverage expertise alongside advanced technology to serve over 1,400 pension schemes and their sponsors. Our goal is to foster a workplace where diverse talents thrive.

Location: London

Employment Type: Permanent, Full Time

Grade: Senior Associate / Consultant

Working Arrangement: Hybrid

Reference: REQ003340

About The Role: Our Data Analytics business continues to grow, and we are now looking for an experienced and technical MLOps Engineer to join our vibrant London office with hybrid 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 Python, SQL, CI/CD and be familiar with Power BI.

XPS Analytics is a specialist and multi‑disciplinary team consisting of actuaries, data scientists 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.

Key Responsibilities:

  • 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‑scale data efficiently. Implement and maintain monitoring of model drifts, data‑quality alerts, scheduled re‑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 XPS to integrate data science findings into practical advice and strategies. Stay abreast of new trends and technologies in Data Science 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 XPS.

Essential Your Profile:

  • 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 Azure Data Factory.
  • Experience in CI/CD and DevOps/MLOps and version control.
  • Familiarity with data visualization and reporting tools, ideally Power BI.
  • 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.

What We Offer:

  • Enjoy a competitive salary, annual discretionary bonus and 25 days’ holiday with buy/sell flexibility.
  • Benefits include pension matching, healthcare plans, life assurance and retailer discounts.
  • We support our team with a flexible benefits scheme, employee assistance, and digital GP service.
  • Participating in volunteering events is encouraged with paid volunteer days available.
  • Referral bonuses are offered for introducing suitable candidates to XPS.

Equal Opportunities Statement: XPS Group is committed to diversity and equal opportunities. We welcome applications from all candidates, irrespective of sex, race, disability, sexual orientation, religion or belief. As a Disability Confident employer, we ensure accessible and supportive work settings for all employees.

Eligibility: Any employment offer made will be conditional upon you satisfying DBS Disclosure checks, Employment or educational references, satisfactory credit checks and eligibility to work in the UK before an offer can be made. XPS Group is not able to provide sponsorship to employees.

MLOps Engineer employer: XPS Group

XPS Group is an exceptional employer, offering a dynamic and inclusive work environment in the heart of London. With a strong focus on employee growth, we provide comprehensive benefits including competitive salaries, flexible working arrangements, and opportunities for professional development within our innovative Data Analytics team. Join us to be part of a forward-thinking consultancy that values diversity and encourages meaningful contributions to the pensions and insurance sectors.

XPS Group

Contact Details:

XPS Group Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land MLOps Engineer

Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at XPS Group. A friendly chat can sometimes lead to job opportunities that aren't even advertised!

Tip Number 2

Show off your skills! Create a portfolio showcasing your MLOps projects, especially those using Azure ML. This gives you a chance to demonstrate your expertise and makes you stand out during interviews.

Tip Number 3

Prepare for technical interviews by brushing up on your Python, SQL, and CI/CD knowledge. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!

We think you need these skills to ace MLOps Engineer

Machine Learning
Azure ML
Python
SQL
CI/CD
Data Management
ETL Processes

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the MLOps Engineer role. Highlight your experience with Azure ML, Python, and CI/CD practices. We want to see how your skills match what we're looking for!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background makes you a great fit for our team at XPS Group. Keep it engaging and relevant!

Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them! Whether it's a machine learning model or a data pipeline, we love seeing practical examples of your work that demonstrate your skills.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to us quickly and efficiently. Plus, it shows you're keen on joining our team!

How to prepare for a job interview at XPS Group

Know Your Tech Inside Out

Make sure you brush up on your technical skills, especially in Python, SQL, and Azure ML. Be ready to discuss specific projects where you've designed, built, or optimised machine learning models. This will show that you not only understand the theory but also have practical experience.

Showcase Your Collaboration Skills

Since you'll be working closely with actuarial analysts and other team members, prepare examples of how you've successfully collaborated in the past. Highlight any multidisciplinary projects you've been part of, as this will demonstrate your ability to work well in a team environment.

Prepare for Scenario-Based Questions

Expect questions that ask you to solve hypothetical problems related to model performance or data management. Practise articulating your thought process clearly, as this will help interviewers see how you approach challenges and make decisions in real-time.

Communicate Clearly with Non-Techies

You’ll need to explain complex machine learning concepts to non-technical stakeholders. Prepare to simplify your explanations and use analogies if necessary. This skill is crucial for ensuring everyone understands the insights derived from your models.