Materials Science Jobs

PhysicsX · New York, United States · US$150,000 – US$250,000 pa

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, backend development of FastAPI microservices in Python, and cloud deployment with Kubernetes, Terraform and AWS/Azure. Requires travel to customer sites for 3-4 weeks per quarter.

PhysicsX · London

Build the simulation side of Large Physics Models, generating training data across fidelity levels and developing solvers in differentiable or GPU-native frameworks like JAX or Warp. Work in a research team alongside ML researchers, using commercial and open-source CFD tools to produce reference data and shape data-generation strategy.

Johnson Matthey · Royston

Installing, maintaining and repairing electrical systems in an industrial plant, covering emergency lighting checks, danger notification remedials, new circuit installs with EIC certification and PAT testing. Works alongside plumbers, carpenters and HVAC technicians to coordinate site services and PPM schedules, with autonomy over wiring routes and equipment positioning.

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 · London

Builds and runs a global partner ecosystem for an AI materials platform, hosting events and managing relationships with tech partners, enterprise clients and research institutions across Europe, the USA and APAC. Bridges external partners with internal AI research, chemistry and product teams, channelling feedback into the agentic platform's roadmap.

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

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.