Materials Science Jobs

ITM Power · Sheffield

Lead supplier quality assurance and development across a PEM electrolyser manufacturer's supply chain, covering supplier approval, auditing, PPAP, FAT and FAIR activities. Drive 8D investigations, KPI-based performance reviews and continuous improvement, working closely with Engineering, Purchasing and Operations and travelling regularly to supplier sites.

CuspAI · London

Builds and grows a global network of partner laboratories that synthesise materials designed with the company's AI platform, working with the Lab Integration team to enable automated, closed-loop discovery workflows. Acts as the operational bridge between partnership, science and AI research teams across Europe, the USA and APAC, and channels lab feedback into platform development priorities.

CuspAI · London

Owns the full lifecycle of data-rich tools, services and web applications, building scalable ingestion, processing and cleaning pipelines for structured and unstructured materials-science data. Develops Python APIs and UIs for querying, exporting and visualising data, with orchestration, governance and containerised deployment using Docker and Kubernetes.

PhysicsX · Singapore

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure. Spans the full stack across complex engineering domains.

CuspAI · London

Owns the design of scientific data representations, schemas and ingestion pipelines that turn heterogeneous external materials data into ML-ready assets. Works with AI researchers and materials scientists to harmonise experimental and computational data from partners, defining quality, validation, lineage and provenance frameworks.

CuspAI · London

Early security hire building automated security pipelines and AI-specific guardrails to protect frontier models, training data and proprietary IP. The role spans securing the ML lifecycle against prompt injection and data poisoning, embedding DevSecOps checks into CI/CD, and hardening cloud and Kubernetes environments with least-privilege IAM.

CuspAI · Cambridge

Trains and evaluates multi-modal foundation models for a materials discovery platform, spanning crystal structures, properties, text and images. Owns a model end to end, from data curation and experiment design through large-scale distributed training to integration, working closely with chemists and materials scientists.

CuspAI · London

Owns a set of partner labs and their integration onto an AI materials-discovery platform, translating experimental workflows, instruments and LIMS/ELN data into engineering requirements. Leads technical discovery and onboarding through to first closed-loop campaigns, and works with ML researchers on Bayesian optimisation campaigns that respect real lab constraints.

CuspAI · London

Develop fast, accurate machine learning force fields distilled into lightweight student potentials for high-throughput Monte Carlo simulation, then integrate them into the in-house kUPS framework. The role involves curating training datasets, running validation campaigns against classical force-field baselines, and profiling the MC inner loop for throughput. Embedded in the chemistry team, with a publication on MLFF-driven GCMC for MOF screening.

CuspAI · London

Designs and builds agentic frameworks that orchestrate closed-loop scientific workflows, connecting agents to ML models, simulation engines and databases. Applies Bayesian optimization and active learning for experimental design, and builds evaluations for agent planning and decision-making. Works closely with chemists and materials scientists on customer projects.