Senior Machine Learning Engineer

Senior Machine Learning Engineer

We are looking for a Senior Machine Learning Engineer to join a global technology organisation and work on data-driven products used by millions of customers worldwide.

You will be part of a cross-functional, international team responsible for building and operating machine learning systems that support personalised customer experiences, marketing communications, content generation and intelligent decision-making.

This is a hands-on engineering role combining machine learning, data engineering, AI and production systems. You will work closely with Data Scientists, Software Engineers and Product teams to take ideas from experimentation through to reliable, scalable production solutions.

About the role

As a Senior Machine Learning Engineer, you will help shape the intelligence behind how, when and what companies communicate to their customers.

Your work will focus on areas such as:

• Decisioning and personalisation - building and improving data foundations and machine learning solutions that optimise customer communications across channels such as email, SMS and push notifications.
• Intelligent customer funnels - supporting initiatives that use data and AI to personalise the customer experience and improve conversion.
• AI-assisted content and search - developing systems for automated content generation, contextual asset retrieval and intelligent support for marketing teams.
• ML infrastructure and tooling - improving the foundations, developer tooling and workflows required to develop, deploy and operate production ML systems at scale.

You will have significant ownership over the systems you build, from initial experimentation and architecture through to deployment, monitoring and continuous improvement.

What you’ll do

• Build, maintain and improve ML infrastructure, repositories, developer tooling and engineering workflows.
• Design and operate data products and machine learning systems from experimentation through to production.
• Build robust data pipelines and integrations supporting machine learning and decisioning systems.
• Develop scalable AI-powered solutions for content generation, search and asset retrieval.
• Build production-grade pipelines and model-serving layers with a strong focus on reliability, latency and observability.
• Work closely with Data Scientists to turn experimental models into robust production services.
• Establish and improve ML engineering standards, CI/CD practices and platform solutions, including technologies such as Databricks and MLflow.
• Monitor production systems, data quality, model performance, drift and latency.
• Diagnose issues under real-world load and implement reliable solutions.
• Take ownership of the systems you build and continuously improve them based on data and user outcomes.
• Collaborate with engineers, data scientists and product stakeholders across international teams.
• Use AI-assisted development tools as part of your everyday engineering workflow.

What you’ll bring

• Strong hands-on experience in Machine Learning Engineering / Data Engineering, ideally with 5+ years of experience building and operating production ML systems.
• Experience taking machine learning models or data products from experimentation into production.
• Strong Python skills and experience with technologies such as Spark and Databricks.
• Experience with ML platforms and tooling such as MLflow.
• Practical understanding of production ML systems, including pipelines, model serving, monitoring and observability.
• Experience working with cloud, platform or backend technologies such as Kafka, Kubernetes or Go would be an advantage.
• Strong statistical literacy and the ability to design and interpret experiments and model metrics.
• Experience working with AI development tools such as Claude Code, Cursor or GitHub Copilot.
• Strong problem-solving and troubleshooting skills.
• A high level of ownership and a pragmatic, delivery-focused mindset.
• The ability to work effectively in a cross-functional and international environment.
• Good product sense and the ability to connect technical solutions with business and user outcomes.

What you can expect

• Work on large-scale, globally used technology products.
• Collaboration with experienced engineers, Data Scientists and Product professionals across international teams.
• A modern technology stack and opportunities to influence architecture and engineering practices.
• End-to-end ownership, from defining problems and experimenting with solutions to deploying and operating them in production.
• A highly collaborative, autonomous and product-oriented working environment.
• Opportunities to work with AI, machine learning and data at significant scale.
• Access to a modern office in Warsaw, with flexible and employee-friendly facilities.

We are looking for people who are curious, pragmatic and enjoy solving complex problems. If you do not meet every requirement but have strong experience in building production ML systems and believe you could thrive in this environment, we would still be interested in hearing from you.