AI​/ML Engineer - Materials Discovery

AI/ML Engineer - Materials Discovery

Contract: Full-time, permanent
Location: Hybrid (London office)
Level
: 2-4 years professional experience

Materiom's mission is to create a world where materials regenerate nature and support human health. We pursue it by building data and AI tools that help discover natural alternatives for packaging, textiles, and the built environment. We support innovators around the world to bring these new materials to market.

We're an interdisciplinary team bringing together materials engineering, computational materials science, AI/ML engineering, and business innovation. In 2026, we're at an inflection point: with advanced AI and an autonomous lab, we are accelerating the discovery of natural materials and supporting innovators across the sector.

This is a high-impact role with the potential to apply leading AI/ML to one of the world's greatest challenges. We're looking for a mid-level AI Engineer to work at the intersection of applied ML,applied AI, and our semi-automated lab; someone excited about the potential of AI for scientific discovery, comfortable with agentic AI, predictive modelling, and keen to work on applying AI for science.

You’ll work within our tech team to contribute across three primary work streams:

• Predictive modelling
  : developing and iterating on ML models that map bio-based formulation design spaces, and building the MLOps infrastructure to support active learning.
• Efficient data sampling techniques: developing and consolidating Bayesian optimization and active learning scientific workflows for experimental & in-silico data generation campaigns.
• Material discovery agentic systems
  : developing and evaluating internal & external tooling that integrate Materiom’s data and model intelligence into AI agents for scientific discovery.

ML modeling & agentic systems

• Design, build, and deploy structure property prediction ML models of bio-based formulations from experimental, in-silico and literature-mined data.
• Develop & instrument internal and external agentic systems with rigorous traceability, performance tracking, and versioning.
• Develop rigorous evaluation pipelines and experiments to compare modelling approaches, interpret results clearly, and iterate against internal performance benchmarks.
• Contribute to MLOps and Software Engineering best practices, including but not limited to versioning, monitoring, evaluation, cost/quality optimisation, CI/CD, Agentic Skills, etc.
• Deploy ML/AI-driven tooling to project partners, pilot users and beyond in order to gather user feedback.

Experimental design & data infrastructure

• Work closely with our engineering and scientific team to design, benchmark, simulate and product ionize efficient data sampling techniques (Bayesian optimization, active learning) to design our experimental and in-silico data generation campaigns.
• Develop, product ionize and maintain data infrastructure, sourcing & storing data from the open-access literature, simulation pipelines, and our semi-automated lab.
• Interface with Materiom’s autonomous lab to debug and improve robotic workflows and data streaming in collaboration with our Research Scientist.

Internal & external-facing collaboration

• Effectively communicate complex technical concepts and findings to multidisciplinary audiences.
• Work closely within the tech team and stay closely attuned to product and scientific priorities, translating them into well-scoped technical work.

You’ll need:

• Genuine excitement about the potential of transforming the materials sector through AI-enabled materials discovery of breakthrough bio-based alternatives
  .
• Master’s degree in a technical field (e.g., Computer Science, Artificial Intelligence, Machine…