Job Vacancy Machine Learning Engineer

Who we are 🩵

We're the people behind global loyalty currency, Avios, and home to three ambitious, growing businesses; and . Each business has its own goals and strategy, but collectively we create brilliant experiences for our global customers.   

We're on a truly exciting journey of growth and transformation - we're going places! This is where you come in.   

The opportunity ✨

You'll be joining our Data Products team, working closely with teams that are aligned to value steams. Our team exists to drive success across Commercial, Customer, Finance and Product domains. We're on a mission to make our data available and usable in one place to delivering powerful data solutions that optimise performance and supercharge decision-making.

We're putting data at the heart of what we do to deliver super experiences to our customers and colleagues with machine learning (ML) foundational to this mission. We looking to embed a centralised AI / ML platform to make our colleagues lives easier when creating value for the company in a standardised way. This platform will enable safe, efficient and reliable training and deployment of ML models.

We are looking for an experienced ML Engineer to help us scale our capabilities to meet the needs of our team and our company's goals. You'll enjoy operating in a hybrid in data science / ML engineering space, with an interest in platform / operations

You will be joining in the early stages of our journey as we build out the infrastructure, tools and processes. We're migrating to Snowflake platform along with other tooling as part of the modern data stack such as AWS (SageMaker). In this role, you will be using ground-breaking technology to build and support world-class AI based products, batch in the near term, and real-time in the future

What you'll get up to 🌠

• Contribute to the design, development, and deployment of our ML platform

• Define and implement best practices for training, evaluating, and deploying machine learning models at scale

• Collaborate with software engineers, data engineers, and data scientists to develop end-to-end AI products & solutions

• Extend and maintain our self-service platform to help our data science teams quickly productionise models following MLOps best practices

What we need from you �'�

• Hands-on experience in data science and machine learning engineering, with a proven track record from design to deployment.

• Extensive knowledge of software development with Python, SOLID principles

• Understanding of machine learning techniques, such as supervised and unsupervised learning, MLOps, and data engineering

• Infrastructure as Code - Terraform or equivalent

• Practical knowledge of AWS, Snowflake, GCP or Azure

• Experience with or equivalent to Snowflake Cortex / AWS Bedrock, AWS MSK, Snowpipe Streaming, Snowpark Container Services

The role has a blended base, between our Central London office and home. We trust you to make the right decision about the type of work that is best done in each location. We expect you'll achieve a 50/50 split between the two and there may be times where you'll want to visit our other locations to tell their stories, too (fully reimbursed).

We might not be right for you if:

• You value perfection over fast iteration and progress; IAG Loyalty moves fast, we learn and iterate as we go; our environment isn't right for everyone.

If you think you have what it takes but don't meet every single point above, please do still apply. We'd love to chat and see if you could be a great fit.

And in return? You'll get access to a whole host of travel, Avios, healthcare benefits and more.  

Equity, Diversity and Inclusion at IAG Loyalty

Our vision, 'to create the world's most rewarding experiences,' applies not only to our customers but for our colleagues too. It's about taking belonging seriously, actively fostering a culture where everyone feels welcomed and valued by embracing diverse identities, personal histories, and perspectives.

This commitment makes IAG Loyalty a rewarding place to work and enhances our ability to solve complex problems, drive innovation, and better serve our customers and communities.

Please let us know if we can make any reasonable adjustments to support your interview process with us.