66 jobs
PhysicsX San Francisco, United States US$150,000 – US$190,000 pa
Delivery-focused role embedding physics-aware AI models into customer tools, building reliable ML data pipelines and working with 3D point-cloud and mesh data. Spans data science and software engineering, translating R&D into reusable libraries and products, with regular on-site customer travel.
PhysicsX New York, United States US$150,000 – US$190,000 pa
Builds and deploys machine learning systems for industrial physics challenges, designing reliable data pipelines and working with 3D point-cloud and mesh data. Partners directly with customers on-site to embed AI models into practical tools, translating R&D outputs into reusable libraries and products. Requires Python, cloud, and MLOps experience with frequent travel.
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.
Cohere London
Own end-to-end technical program delivery for UK public sector and defence customers, from initial deployment through production scaling, acting as the bridge between frontier AI capabilities and government requirements. Navigate procurement, security authorisations, data sovereignty and compliance while coordinating Applied ML, Forward Deployed Engineering, Platform and Product teams. Work spans air-gapped, on-premises and highly regulated environments.
ElevenLabs United Kingdom
Backend-leaning full-stack role building and maintaining a platform on top of cutting-edge voice models used by millions, adding product functionality and integrations, and strengthening internal infrastructure for scale, performance and security. Engineers collaborate with Frontend, Growth and Sales teams, with flexible project staffing across the company.
ElevenLabs United Kingdom
Builds and operates core platform foundations covering workspaces, user management, API keys, login, analytics and admin tooling, or generic resource and permissioning services used by product teams. Owns features end to end from backend services to settings UI, with safe rollout and migration of live, business-critical systems serving millions of users.
PhysicsX London
Owns PX's 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 Talent on employer brand storytelling. Works cross-functionally with engineers, designers and external agencies in a fast-moving, high-ownership comms team.
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
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.
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 full-stack work with Python, FastAPI REST APIs and microservices, plus cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. Expects travel to customer sites in Asia, North America and Europe for 3-4 weeks per quarter.
PhysicsX Singapore
Builds and delivers high-fidelity multi-physics CFD models, from geometry clean-up and meshing to simulation and post-processing, integrating experimental data for validation. Automates parametric CAD and simulation pipelines for design optimisation and DoE, generating datasets for machine learning surrogates. Works on-site with customers and mentors junior colleagues, with global travel up to 2-3 weeks per quarter.
PhysicsX Singapore
Lead technical delivery of physics AI solutions, architecting deep learning models and optimisation methods to predict and control physical systems. Build scalable production data pipelines, mentor junior team members, and collaborate on-site with customers across multiple regions to embed AI models into engineering tools.
PhysicsX Singapore
Lead the deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimisation) into customer production environments. Own scoping, architecture and success metrics for data/ML systems, mentor engineers, and work on-site with customers across North America, Europe, Asia and Oceania for 3-4 weeks per quarter.
PhysicsX Singapore
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 of Python/FastAPI REST APIs and microservices, and cloud deployment using Kubernetes, Helm, Terraform and AWS/Azure. It suits someone who can grasp complex engineering problems across industries and own solutions end-to-end.
Cohere London
Designs and writes high-performance, scalable software for training frontier models, improving the training setup from an infrastructure and codebase performance standpoint. Builds tooling to speed up training cycles and works on supercompute and data infrastructure, bridging research and production. Works with distributed training stacks like Kubernetes, Slurm and Ray, with one of the highest compute-to-engineer ratios in the world.
