Data Science ML/GenAI Engineer (FRE/ ENG)
Develops and productionizes machine learning and GenAI solutions, improving data pipelines and existing code while collaborating across data and application teams to deliver reliable, scalable capabilities.
About ENPICOM
ENPICOM brings together cross-domain expertise in biology, software, and AI to simplify complex workflows into intuitive solutions that scientists love to use. We build the scalable digital platform that provides the foundation of harmonized, actionable data necessary to operationalize AI. By empowering scientists to easily access and apply AI models for analysis and decision-making, we enable them to develop breakthrough medicines faster and more effectively.
The role
We are looking for a Machine Learning Scientist to join our Bioinformatics & AI team. You will help develop machine learning models that speed up the discovery and optimization of therapeutic antibodies, and you will help turn those models into reliable tools that our customers use every day on the ENPICOM platform.
This role is a good fit if you enjoy both sides of the work: understanding a scientific problem deeply, and making sure the solution actually runs well in practice. You will also help extend the AI capabilities of the platform, including newer approaches such as AI agents that can carry out analysis steps on a scientist's behalf.
You will work closely with experienced ML scientists, bioinformaticians and software engineers, and you will have room to grow your skills in antibody biology, model deployment, and modern AI tooling.
What you will do
Evaluate, adapt, and train deep learning models for antibody engineering tasks, such as predicting antibody properties or suggesting improved protein variants.
Compare published and in-house models on our data and help decide which ones are worth bringing to the platform.
Turn promising models into robust, tested services: packaging, versioning, monitoring, and keeping them running well over time.
Help build AI features on the ENPICOM platform, including agent-based tools that connect models and analysis workflows.
Design sound experiments and use statistics to check whether a model really works, and where it does not.
Work with bioinformaticians and scientists to understand the biology behind a problem and to explain results clearly to non-specialists.
Keep up with new methods in machine learning for proteins and antibodies, and share what you learn with the team.
Mentor junior colleagues and interns, helping them grow their skills and sharing what you know.
What we offer
Work that matters: your models help bring better antibody medicines to patients.
A small, friendly team where your work quickly makes it into a product used by scientists around the world.
A competitive salary based on your experience.
Location: 's-Hertogenbosch, the Netherlands, hybrid with 1 to 2 days per week in the office.
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