Senior Machine Learning Engineer at Lever Scott International

We are supporting a large international organisation that is continuing to scale its enterprise AI and Machine Learning capabilities.

As part of a wider AI transformation programme, they are building and productionising ML services on a large-scale Databricks platform, primarily hosted within AWS.

They are looking for an experienced Senior Machine Learning Engineer who combines strong software engineering principles with hands-on Databricks and Machine Learning expertise.

The Role

You will:

• Design, build and productionise Machine Learning services within Databricks using Python, SQL and Linux.
• Build scalable ML solutions that can move effectively from experimentation into production.
• Work with cross-functional Data, AI and Software Engineering teams to deliver scalable Data Science and Machine Learning projects.
• Take ownership of production ML services, ensuring reliability, performance and continuous business value.
• Develop and improve engineering standards, reusable components and best practices across the Databricks platform.
• Optimise workloads and services with a focus on scalability, performance and cloud cost efficiency.
• Write clean, maintainable and production-quality code, including testing and debugging.
• Work closely with adjacent engineering teams across cloud infrastructure, Data Engineering, CI/CD, governance, data provisioning and orchestration.
• Contribute to the continued development of the organisation's wider AI and Machine Learning platform.

What We're Looking For

• Strong commercial experience as a Machine Learning Engineer, ideally within large-scale or complex environments.
• 2+ years of hands-on experience building Machine Learning solutions on Databricks.
• Experience across the Databricks ecosystem, ideally including technologies such as Unity Catalog, MLflow and Databricks Asset Bundles or comparable tooling.
• Strong Python development experience.
• Strong understanding of SQL and relational databases such as MS SQL, MySQL, HANA, PostgreSQL or similar.
• Strong broader Software Engineering experience, ideally 5+ years.
• Experience deploying and operating production-grade Machine Learning services.
• Strong understanding of Apache Spark and distributed data processing.
• Experience working within a major cloud environment. AWS is the primary environment, although strong Azure or GCP experience is also relevant.
• Experience with CI/CD and modern DevOps practices, regardless of the specific tooling used.
• Good Linux knowledge and experience working within production environments.
• Strong problem-solving skills and the ability to work effectively across technical teams.
• Professional English communication skills.

The Programme

This is an opportunity to join a significant enterprise AI and Data transformation programme, focused on building the engineering and platform capabilities required to deploy Machine Learning at scale.

The core environment combines Databricks, AWS, Machine Learning Engineering, Data Engineering and modern DevOps practices.

The organisation is particularly interested in engineers who understand how to take Machine Learning beyond experimentation, building the software, infrastructure and engineering practices required to operate reliable ML services in production at enterprise scale