62 jobs for “Energy Transition”
PhysicsX New York, United States US$200,000 – US$250,000 pa
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.
PhysicsX New York, United States US$120,000 – US$240,000 pa
Builds and deploys deep learning and probabilistic models to predict and control physical systems, working alongside simulation engineers and customers. Owns data pipelines and production-ready models, and travels to customer sites 3-4 weeks per quarter to co-develop solutions on-site.
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
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.
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, 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.
PhysicsX Singapore
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.
PhysicsX New York, United States
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.
PhysicsX New York, United States US$200,000 – US$300,000 pa
Owns chemistry capabilities end to end, setting technical direction and leading a team across capability-building and customer delivery. Couples atomistic and molecular insight into continuum and systems-scale models, spanning DFT, machine learning interatomic potentials, and multiscale simulation for industrial materials and process problems.
PhysicsX London
Owns chemistry capabilities end to end, setting technical direction and leading a team across capability-building and customer delivery. Couples atomistic and molecular insight into continuum and systems-scale models, spanning DFT, machine learning interatomic potentials and process simulation for industrial materials problems.
PhysicsX Singapore
Join a new Singapore research team building physical foundation models for industrial engineering, translating physics and simulation challenges into mathematical formulations. You will train deep learning and probabilistic models on large spatiotemporal, geometric and point-cloud datasets, run experiment pipelines, and publish and present results with customers and partners.
PhysicsX Singapore
Build physical foundation models for industrial engineering, scaling training to large datasets on multi-GPU cloud compute. Turn research prototypes into robust, optimised implementations, own research workstreams, and translate results into reusable libraries and tooling alongside scientists and customers.
PhysicsX London
Owns the editorial calendar and writes blog posts, web pages, thought leadership, scripts and event materials, translating deep technical work into clear narratives. Leads LinkedIn and Instagram, supports executive and technical speaking engagements, and partners with engineers, designers and external agencies on video and joint content.
PhysicsX London
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.
PhysicsX Singapore
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.
