AI Engineer
London Area, United Kingdom Full-time Posted 14 hours ago
Company Description Materiom’s mission is to accelerate the discovery of breakthrough bio-based materials that can replace conventional plastics. The organization envisions materials that safely return to nature, enriching soils, supporting carbon drawdown, and nourishing ecosystems instead of creating pollution. Materiom focuses on Earth’s most abundant renewable, biomass-derived macromolecules as an under-explored frontier in materials science. By building open knowledge and AI-enabled tools, it supports a global community of early-stage researchers and leading organizations working on the materials transition. Team members join a purpose-driven environment at the intersection of AI, sustainability, and materials innovation.
Role Description As an AI Engineer at Materiom, you will design, implement, and deploy machine learning models to accelerate the discovery and optimization of bio-based materials. You will work closely with materials scientists and data engineers to understand domain problems, define data requirements, and build end-to-end pipelines from data preprocessing to model evaluation and deployment. Day-to-day responsibilities include developing and training neural network architectures, experimenting with pattern recognition approaches, and applying techniques such as NLP to extract insights from scientific literature, experimental records, and other unstructured data sources. You will contribute to scalable software components, APIs, and tools that integrate AI models into Materiom’s platform and workflows, while writing clean, maintainable code and tests. This is a full-time, hybrid role based in the London Area, United Kingdom, with a mix of on-site collaboration and the flexibility to work from home part of the week.
Qualifications
Role Description As an AI Engineer at Materiom, you will design, implement, and deploy machine learning models to accelerate the discovery and optimization of bio-based materials. You will work closely with materials scientists and data engineers to understand domain problems, define data requirements, and build end-to-end pipelines from data preprocessing to model evaluation and deployment. Day-to-day responsibilities include developing and training neural network architectures, experimenting with pattern recognition approaches, and applying techniques such as NLP to extract insights from scientific literature, experimental records, and other unstructured data sources. You will contribute to scalable software components, APIs, and tools that integrate AI models into Materiom’s platform and workflows, while writing clean, maintainable code and tests. This is a full-time, hybrid role based in the London Area, United Kingdom, with a mix of on-site collaboration and the flexibility to work from home part of the week.
Qualifications
- Strong foundation in computer science and software development, including data structures, algorithms, version control, and collaborative coding practices.
- Hands-on experience with machine learning and pattern recognition, with the ability to design, train, and evaluate models on complex scientific or technical datasets.
- Practical expertise in neural networks and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX), including model tuning and optimization.
- Experience with Natural Language Processing (NLP), such as literature mining, information extraction, or building text-based models to work with scientific or technical documents.
- Proficiency in Python and common data/ML ecosystems (e.g., NumPy, pandas, scikit-learn), and familiarity with building reproducible ML workflows.
- Comfort working with heterogeneous and imperfect scientific data, including data cleaning, feature engineering, and validation.
- Bachelor’s or higher degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field, or equivalent practical experience.
- Ability to communicate technical concepts clearly to cross-functional partners and collaborate in an interdisciplinary, mission-driven team.
- Experience or interest in materials science, sustainability,
