33 jobs
PhysicsX New York, United States US$150,000 – US$250,000 pa
Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development with Python/FastAPI microservices, and cloud deployment using Kubernetes, Terraform and AWS/Azure, with frequent on-site travel to customer sites.
PhysicsX London
Build the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develop solvers in differentiable or GPU-native frameworks like JAX or Warp, using commercial and open-source CFD tools, while collaborating closely with ML researchers in a research team.
Cohere London
Hands-on research and engineering role on the Agent Code team, developing code-generating LLMs and autonomous agent systems for enterprise use. Involves training code models, building agent frameworks for inference and sampling, creating SFT trajectories, working on RL algorithms, and designing benchmarks, in collaboration with the pretraining team on frontier compute infrastructure.
Cohere London
Drive safety research for agentic LLMs, focusing on data generation, post-training algorithms and evaluation methods so models that access external tools and act in the world remain fair, trustworthy and secure. Work with cross-functional ML, data annotation, product and policy teams on a small, autonomous team, requiring strong statistics, software engineering and Python/PyTorch skills.
PhysicsX London
Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments, using Python, PyTorch, Pandas, fastAPI, Scipy and Kubeflow across cloud and on-prem. Leads scoping and architecture for data/ML systems, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter.
PhysicsX London
Builds and runs high-fidelity CFD models, from geometry clean-up and meshing through simulation and post-processing, using tools such as Star-CCM+, OpenFOAM or Fluent. Works with data scientists and ML engineers to generate simulation datasets for deep learning surrogates, and supports customer engagements with occasional travel. Based in London with 2-3 days per week in the central office.
PhysicsX London
Own a research work-stream at the frontier of 3D geometry representation and generation, designing and training generative models over geometry and closing the coupling between geometry and physics. Work against production numerical solvers so model quality is measured in validated physics, collaborating with ML and simulation engineers and customers.
Cohere London
Builds reinforcement learning environments for enterprise AI agents, populating them with hard tasks, plausible data and reward verifiers, then runs agents inside to evaluate and train them. Works across modelling and product to find capability gaps, and partners with external vendors on expert-built environments and quality tooling.
Cohere London
Forward deployed engineer building and shipping LLM-powered agentic workflows for enterprise customers, from early prototypes to production-grade agents. Works directly with clients in finance, healthcare and telecoms, integrating models with tools, APIs and sensitive data, and contributing features to Cohere's North AI workspace platform.
Cohere London
Designs next-generation evaluation benchmarks and infrastructure to measure LLM progress, including training LLM judges, refining data synthesis pipelines, and improving evaluation efficiency. Works cross-functionally to turn model feedback into trustworthy, repeatable evaluations, and builds scalable tools for probing model performance.
