Machine Learning Engineer

Location: Wroclaw, (flexble remote/hybrid working)

Permanent Employment, package competitive and bonus

We are recruiting on behalf of our clients, leading global healthcare organisation, who, at the forefront of digital health innovation, is seeking an experienced ML Engineer to join their AI and Data Science Team.

They are pioneering next-generation natural language health information products and applications, leveraging cutting-edge AI, machine learning, and natural language understanding (NLU) to make healthcare smarter, safer, and more human-centered.

This is a rare opportunity to work alongside world-class researchers, engineers, and clinicians on technologies that improve patient outcomes and empower healthcare professionals globally.

The Impact You’ll Make in this Role

As a Machine Learning Engineer, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative and diverse people around the world. Here, you will make an impact by:

Collaborating cross-functionally with domain experts, data scientists, and stakeholders to translate business requirements to technical requirements

Implementing automated pipelines for data processing and the training, evaluation and deployment of deep learning or LLM models including Agentic AI

Designing scalable infrastructure for model training and inference, both in the cloud and on-premises

Setting up monitoring to enable the implementation proactive countermeasures for model degradation

Enabling data privacy and compliance with healthcare regulations such as GDPR and HIPAA during model development and deployment

Your Skills and Expertise

Master's degree or PhD in computer science, mathematics or related fields or Bachelor’s degree with at least 5 years of experience

Experience creating engineering solutions that support an AI / ML model’s lifecycle including data ingestion, training, evaluation, and deployment

Familiarity with a cloud provider, preferably AWS

Proficiency in large-scale data processing technologies, such as Hadoop and Spark

Hands-on experience with scalable model deployment, e.g., using Docker and Kubernetes

Capability of providing maintainable and reusable code including source control with Git, unit and integration testing and a solid knowledge of CI/CD concepts

Additional qualifications that could help you succeed even further in this role include:

Solid understanding of Machine Learning methods

Familiarity with the integration of LLMs and Agentic AI into real-world software solutions, for example via MCP. Demonstrated ability of working in interdisciplinary environments