Senior Machine Learning Engineer

Lever Scott International; Berlin; Vor Ort; EUR 85.000 - 115.000; Vollzeit

Zusammenfassung

Lever Scott International is seeking a Senior Machine Learning Engineer to design and productionise ML services on a Databricks platform hosted in AWS. You will collaborate with Data, AI and Software teams to deliver scalable ML projects and own production ML services.

The role focuses on building reliable, maintainable ML infrastructure and code, with emphasis on performance, cost efficiency and engineering standards across the Databricks ecosystem.

Qualifikationen

• Significant commercial ML engineering experience in large-scale environments.
• 2+ years building ML solutions on Databricks.
• Experience with Unity Catalog, MLflow or similar tooling.
• Strong SQL skills with relational databases (MS SQL, MySQL, PostgreSQL).
• 5+ years software engineering experience and production deployment.
• Proficient in Python and Linux in production
• Experience with AWS and CI/CD practices.
• Excellent problem-solving and cross-team collaboration.

Aufgaben

• Design, build and productionise ML services within Databricks using Python, SQL and Linux.
• Develop scalable ML solutions from experimentation to production.
• Collaborate with Data, AI and Software Engineering teams on ML projects.
• Own production ML services, ensuring reliability, performance and value.
• Improve engineering standards and reusable components on the Databricks platform.
• Optimise workloads for scalability and cloud cost efficiency.
• Write clean, testable production code and debugging processes.
• Coordinate with cloud infra, Data Eng, CI/CD, governance and orchestration teams.
• Contribute to the ongoing development of the organisation's AI/ML platform.

Kenntnisse

Machine Learning Engineer

Databricks

SQL

Python

Linux

Spark

Cloud AWS

CI/CD

Production ML

Problem-solving

English Communication

Tools

Databricks Unity Catalog

MLflow

Databricks Asset Bundles

MS SQL

MySQL

PostgreSQL

Jobbeschreibung

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 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