Materials Discovery AI Engineer — Impact & Innovation

HireAlice; Greater London; Hybride; GBP 63 000 - 77 000; Plein temps

Avantages offerts par ce poste

30 days paid holiday

Skills development budget

Bike2Work scheme

Flexible office/remote work

Company retreats

Résumé du poste

Materiom in London is seeking a skilled AI/ML engineer to design, build, and deploy structure-property prediction models for bio-based formulations. You will work with experimental, in-silico, and literature data, collaborating with scientists to define features and evaluation criteria.

You will implement end-to-end pipelines, contribute to LLM-based agents, and help maintain MLOps practices, cloud deployments, and reproducible experiments, while communicating complex concepts to

Qualifications

• Genuine excitement about AI-enabled materials discovery in bio-based systems.
• Strong ML fundamentals, validation, and uncertainty estimation.
• Experience with end-to-end ML-powered systems and model deployment.
• Proficiency with PyTorch, scikit-learn, MLFlow, and cloud platforms.

Responsabilités

• Design, build, and deploy structure-property prediction ML models.
• Quantify model confidence and guide experiments or simulations.
• Collaborate with scientists on features, data standards, and targets.
• Develop, operate, and maintain data extraction, training, and orchestration workflows.

Connaissances

ML fundamentals

Python

PyTorch

scikit-learn

LLM-based agents

Data curation

Cloud platforms

Formation

Master’s degree in Computer Science/AI

Outils

PydanticAI

CrewAI

Google ADK

Description du poste

Materiom in London is seeking a skilled AI/ML engineer to design, build, and deploy structure-property prediction models for bio-based formulations. You will work with experimental, in-silico, and literature data, collaborating with scientists to define features and evaluation criteria.

You will implement end-to-end pipelines, contribute to LLM-based agents, and help maintain MLOps practices, cloud deployments, and reproducible experiments, while communicating complex concepts to