MLOps Engineer

Job Description

We want to expand our Data Science function further within our well-established strong data-driven Centralised Analytical department. Our Data Science mission is to build machine learning models in the production environment relative to Marketing, Customer Insights, and Safer Gambling and establish a strong culture of data-driven decision-making in our organisation’s strategy.

We are looking for an experienced MLOps Engineer to support the delivery of ML products. You will work closely with the Data Science team to understand the data and product requirements. You will also collaborate with the Data & Ops team to stay on top of key changes that may impact the ML frameworks and to own the release of ML products. We use Azure Databricks as our platform.

To be successful in the role, you will need to be experienced in cross-team collaboration to deliver data science projects whilst promoting best practices. You will be proactive in identifying and communicating data-related issues and will act as the interface between Data Science and Data & Ops teams.

The Data Science department is currently a smaller team, with an ambition to grow, with a mix of Data Scientists and ML engineers. Therefore, it is an excellent opportunity to grow, contribute and challenge yourself.

Core Responsibilities

• Development and maintenance of the ML data pipeline, with the proper quality controls and contingency plans in place
• Model deployment & serving, ensuring that solutions align with internal best practices and have a high degree of automation
• Cost control, having both the data production and solution deployment as efficiently as possible
• Cross-team collaboration, communicating all key elements that impact the well-functioning of the ML solutions

Qualifications

• Postgraduate degree in a relevant discipline (e.g. IT, STEM, Maths, Computer Science) or equivalent experience
• Good data modelling, software engineering knowledge, and strong knowledge of ML packages and frameworks
• Skilful in writing well-engineered code using Spark, and advanced SQL and Python coding skills
• Experienced in working with Azure Databricks
• Proven experience working with Data Scientists to deliver best in-class solutions for model deployment and monitoring
• Great technical and communication skills, with a high degree of proactivity
• Passion for learning and keeping abreast of new technologies and data models

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