Lead Machine Learning Engineer (3-6 month contract)

at  onefive GmbH

HOW YOU’LL HELP BUILD ONE•FIVE

Develop our core AI Engine

• You’ll bring state-of-the-art AI research from concept to implementation to create AI-driven applications with a direct impact on our packaging development processes.
• You’ll work closely with stakeholders and other engineers to evaluate and optimize our systems for performance and accuracy and ensure they are production-ready.

Coordinate ML requirements with stakeholders

• Surface requirements to other teams (data engineers, domain experts and software engineers) to ensure data harvesting and processing aligns with our AI development needs.

ABOUT US

Protecting our planet by developing materials for clean & closed material loops.
About Us Vide

Please note, due to the senior and unique nature of this role we ideally require someone with a strong scientific background (i.e. BioChemistry, Chemistry or Physics) or experience handling and processing large amounts of raw scientific data, as you’ll be developing machine learning and LLM systems based on materials engineering.
As we continue to grow into 2025 and beyond, we’re looking for an experienced freelancer to help us develop our Packaging Development AI Engine.
The role will involve integrating our current data and previously built prediction models to an AI system recommender. As an experienced Machine Learning Engineer, you will use your skills to develop and integrate new AI and ML approaches to power our internal Material Science Platform.
We’re looking for an experienced engineer skill in not only architecting and building similar systems, but then also providing additional monitor for performance and model maintenance, helping deploy the successful and efficient models into production.
You’ll also be designing AI agents that emulate scientific reasoning. Domain expertise is essential for accurately developing, interpreting, and managing these systems.
In a startup environment, you’ll need to work independently, applying advanced ML techniques to complex, scientifically-sourced data to ensure robust performance.
Given the remote first nature of our team, this role can be based anywhere but willing to work approx UTC/UTC+2 core hours, in order to overlap with the bulk of our European based team.