ML Ops Engineer

Our Ways of Working Principles:

We believe that most of us do our best work when we work together, but we know that everyone works in different ways, and quite frankly, has other commitments and responsibilities outside of work.

As we further adjust to hybrid working, we want to take what we've learnt from working remotely and keep the flexibility that's enabled us to thrive and keep driving our business forward.

We have some core principles which support us in this:

Do what’s right

Trust & give permission

Delivery matters

We understand ways of working can look different based on your role, team and you as an individual so we are here to support and discuss this with you during the interview process.

Work with us

At Moonpig Group our mission is to help people connect and create moments that matter. We’re an international group made up of three brilliant brands – Moonpig in the UK, Ireland, US and Australia, and Greetz in the Netherlands – with our newest addition Buyagift joining us in 2022.

We were founded with a goal to disrupt the traditional greetings industry. Two decades on, we’re an established leader within the online gifting market, offering a wide range of products to customers across the world.

Moonpig is an iconic brand and innovator, with clear values (read more about our values here!). These values set our teams and our business up for success in an environment that’s fun, supportive and challenging. They’re the glue that binds us together and we think of them as a platform to help us deliver our best work. You have every chance to drive impact here at Moonpig, and most importantly, we genuinely want you!

Our architecture is built for scale and flexibility which will allow us to quickly innovate and launch new propositions - coupling that with the wealth of data we have on our customers, the sky's the limit in the world of experimenting with cutting edge ideas.

What you’ll be doing

 Join our innovative team as an MLOps Engineer, where you will play a crucial role in building and maintaining scalable machine learning infrastructure. You will collaborate closely with data scientists, engineers, and business stakeholders to streamline the end-to-end machine learning lifecycle, from model development to deployment and monitoring. Your work will ensure the seamless integration of ML models into production systems, leveraging cutting-edge technologies and cloud platforms to optimise performance, automate workflows, and ensure reliability. This is an exciting opportunity to make a direct impact on the future of data-driven solutions within our organization.

The role sits within the ML Ops team, which is part of the Data Platform Team, and wider Data function. The position reports into the Engineering Manager for ML Ops and Data Engineering.

Key Responsibilities:

• Model Deployment and Management: Design, implement, and manage CI/CD pipelines for the deployment of machine learning models into production environments, ensuring scalability, reliability, and performance.
• Infrastructure Automation: Build and maintain the infrastructure for data pipelines, model training, and model serving using a cloud platform (AWS) and infrastructure-as-code tools (Terraform).
• Monitoring and Optimization: Implement monitoring systems for models in production to track performance, detect anomalies, and automate model retraining workflows.
• Collaboration with Data Teams: Work closely with data scientists, data engineers, and software developers to streamline the end-to-end machine learning lifecycle, from experimentation to productionisation.
• Scalability and Performance Tuning: Optimise machine learning workflows for performance and scalability, including resource utilisation, distributed processing, and GPU/TPU acceleration.
• Model Versioning and Governance: Implement and manage version control for models and datasets, ensuring compliance with industry best practices for reproducibility and traceability.
• Automation of Workflows: Develop automated workflows for model testing, validation, and deployment, integrating with CI/CD tooling.
• Security and Compliance: Ensure security best practices are followed, including managing access control, data privacy, and compliance with relevant regulations.
• Tooling and Framework Selection: Evaluate, integrate, and implement appropriate ML Ops tools and frameworks to enhance the efficiency of machine learning operations, including experiment tracking (e.g., MLflow) and model serving platforms (e.g., Sagemaker).

You'll be a great addition to the team if you:

• Experienced in building cloud/serverless applications, using Python, on AWS.
• Have experience working with Machine Learning tools, building pipelines to productionise ML model deployment. 
• Experience with CI/CD.
• Enjoy being part of an engineering team, working closely with people of different specialisms across the business.
• Are willing to challenge your own ideas; to try, fail, learn and repeat. You encourage others to do the same
• Prefer a collaborative environment, sharing knowledge through collaboration, pair programming and constructive code review.
• Have an awareness of cloud security and work effectively with our internal security team

Our Data Tech Environment:

• AWS (inc Sagemaker, EC2, Lambda, Glue, S3, API gateway), Snowflake, Terraform, Python, C#, .NET Core, SQL.
• GitHub for SCM, CI/CD through GitHub workflows.
• DBT, Google Analytics, GTM, GCP Big Query, Fivetran, Airflow, Metaplane.
• Robust and performant cloud/serverless applications.

We don’t expect you to have experience with all of the technologies above!

How we get there:

• Kanban
• Jira / Confluence
• Grafana and AWS Cloudwatch
• Clean Architecture
• TDD
• Pair Programming
• Focus on experimentation to validate our hypothesis

Want to hear more? 

Find out more about Moonpig Group and what it has to offer here!

Moonpig’s Commitment to Equality, Diversity and Inclusivity 

At Moonpig Group, we’re committed to creating an inclusive and caring culture with brilliant people who feel a real sense of belonging. We welcome and celebrate all diverse backgrounds to Moonpig Group, from working parents who need flexibility with their hours to individuals who are neurodiverse and prefer to work a certain way.

We’re proud to have several employee-led committees within our organisation, including the LGBTQ+, Gender Balance, Neurodiversity and our EMBRACE (Educating Myself for Better Racial Awareness and Cultural Enrichment) Committees.

We’ll continue to push for diversity and that sense of belonging so that all Moonpig Group employees feel safe and comfortable to be their true authentic self at work.