Materials Science Jobs

• New York, United States
• Hybrid
• US$200,000 – US$300,000 pa
• Lead

Partners with engineering teams to embed security into CI/CD pipelines, lead threat modeling and secure design reviews for web apps, APIs and cloud services, and manage the product vulnerability lifecycle. Requires deep DevSecOps and application security expertise, with hands-on Python and Go development and SAST tooling.

GitHub · GitLab · Semgrep +6

• New York, United States
• Hybrid
• US$200,000 – US$250,000 pa
• Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +6

• London
• Hybrid · 3 days in office
• Mid-level
• Permanent

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.

NVIDIA · Meta

• Bristol
• On-site
• Entry level
• Internship

A four-year apprenticeship in the Structures Test Team at Airbus's AIRTeC facility, supporting test campaigns on aircraft structures. Apprentices rotate through mechanical, electrical and instrumentation work — machining, assembly, sensor installation, metrology and data acquisition — with an option to specialise in calibration and metrology. Year one combines study at Weston College with two days a week on site.

Lathes · Mills · Surface Grinders +6

• 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, RESTful APIs in Python (FastAPI), microservices and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure, plus 3-4 weeks of travel per quarter to customer sites.

FastAPI · Helm · Kubernetes +3

• Singapore
• Mid-level

Contributes to high-fidelity CFD simulations for marine propulsion projects, including propeller and hull-propeller interaction, using OpenFOAM for steady-state and transient cavitating cases. Builds models from geometry clean-up and meshing through post-processing, and works at the intersection of CAE and data science to generate simulation datasets for machine learning surrogates. Joins at the founding stage of the Singapore team, collaborating with data scientists, ML engineers and customers.

OpenFOAM · Star-CCM+ · Fluent +4

• Singapore
• Mid-level

Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate industry challenges into product opportunities, tracking engagement and measuring value. Suits a technical background in data science/ML or engineering.

• New York, United States
• Hybrid · 2–3 days in office
• Mid-level

Builds and runs high-fidelity CFD models from geometry clean-up and meshing through simulation and post-processing, using Star-CCM+, OpenFOAM or Fluent on cloud and HPC resources. Works with data scientists and ML engineers to generate simulation datasets for deep learning surrogates, supporting customer engagements with occasional international travel.

Star-CCM+ · OpenFOAM · Fluent +4

• Singapore
• Senior

Builds and applies advanced thermal, chemical and multiphase CAE models in Abaqus, ANSYS or COMSOL, coupling heat transfer with fluid, diffusion and electrostatic phenomena. Works directly with customers, often on-site, instrumenting physical processes to generate validation data and integrating models into AI tools. Combines shop-floor manufacturing experience with Python/Java automation and parametric CAD.

Abaqus · ANSYS Mechanical · ANSYS Fluent +4

• London
• Hybrid · 3 days in office
• Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, forecasting, anomaly detection) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture, mentors engineers, and travels to customer sites roughly 3-4 weeks per quarter.

Python · PyTorch · Pandas +6

• Singapore
• Lead

Deliver high-fidelity multi-physics CFD simulations for industrial customers, from geometry clean-up and meshing to post-processing and validation against experimental data. Build parametric CAD models and automate simulation pipelines for design optimisation and DoE studies, generating datasets for machine learning surrogates. Work alongside data scientists and ML engineers, mentor junior colleagues, and travel globally up to 2-3 weeks per quarter to work on-site with customers.

Star-CCM+ · OpenFOAM · Fluent +3

• Singapore
• Lead

Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimization—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.

Python · PyTorch · Pandas +6

• Singapore
• Senior

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.

FastAPI · Helm · Kubernetes +3

• New York, United States
• Hybrid
• US$240,000 – US$300,000 pa
• Director · manages people

Leads regional deployment engineering for a physics AI platform, owning end-to-end delivery into customer-owned infrastructure and acting as primary technical contact for CIOs and CTOs. Combines executive engagement with hands-on work on Kubernetes, cloud and infrastructure-as-code deployments, while hiring and scaling the regional team. Requires navigating regulated, high-security and on-prem/HPC environments.

Kubernetes · AWS · Azure +6

• Singapore
• Hybrid
• Lead

Develops high-fidelity multiphase CFD and DEM models for industrial bioprocess and chemical engineering applications, covering gas-liquid, solid-liquid, VOF and Euler-Euler/Euler-Lagrange approaches. Owns the full simulation pipeline from geometry clean-up and meshing through solver setup, HPC runs and experimental validation, while building parametric CAD and Python automation for design optimisation and AI surrogate workflows.

Star-CCM+ · OpenFOAM · Fluent +5