Jobs at PhysicsX

Build and own backend platform capabilities enabling data scientists, machine learning engineers, and simulation engineers to create, train, and deploy physics-informed models. Collaborate cross-functionally with backend, frontend, design, data science, and simulation teams. Develop scalable, observable production software using Python and Go, including testing, containerization, CI/CD, authentication, event-driven messaging, and Kubernetes-based applications.

Lead regional deployment engineering for PhysicsX, owning end-to-end on-prem and cloud deployments of a Kubernetes-based platform. Serve as Field CTO with executive customer engagement, manage deployment programs, navigate security/compliance, enable platform releases, and hire/scale the deployment team while stepping in hands-on for complex technical challenges.

The Principal Simulation Engineer leads simulations, collaborates with customers to solve engineering challenges, and mentors junior colleagues while managing complex multi-physics models and workflows.

The Senior ML Infrastructure Engineer will manage and optimize the ML infrastructure, focusing on training pipelines, model serving, and collaboration with research teams.

Support transactional finance across UK, US and Singapore entities: manage and approve employee expenses, reconcile receipts and bank accounts, resolve discrepancies, and provide ad-hoc finance support to keep records audit-ready.

Lead global revenue recognition, manage multi-jurisdiction tax and statutory reporting (UK/US/Singapore), own AR processes, support audits, maintain technical accounting (leases, share-based payments), and improve controls and financial processes across the group.

The Senior Simulation Data Engineer will manage the end-to-end data pipeline for simulation, ensuring high-quality outputs for ML training and collaborating with research teams to optimize processes.

The Machine Learning Engineer will design and implement scalable ML pipelines, work with 3D data, and collaborate directly with clients on engineering challenges, ensuring solutions are effective and impactful.

As a Forward Deployed Software Engineer, you will develop applications leveraging physics AI models, collaborating with data scientists and customers, and design E2E solutions while deploying APIs and microservices.

Build and post-process CFD models, including geometry cleanup, meshing, simulation, and results analysis. Support parametric CAD, workflow automation, design optimization, and simulation dataset generation for machine learning models. Collaborate with data scientists, machine learning engineers, and customers, using cloud and HPC resources. Prepare customer presentations, apply engineering best practices, and travel occasionally for customer engagements.

Lead cross-functional strategic programs, translate company goals into executable plans, support annual and quarterly planning, track OKRs and operational metrics, identify organizational pain points, and drive alignment across teams. The role also involves competitive intelligence, stakeholder communication, ROI measurement, retrospectives, and building durable systems that improve company performance as PhysicsX scales.

The Office Manager oversees daily office operations, manages vendor relationships, ensures health and safety compliance, and champions employee experience initiatives. They serve as the primary point of contact for office-related queries and collaborate on operational improvements with global teams.

Lead development and deployment of deep learning and probabilistic models for multi-physics engineering problems. Architect scalable data pipelines, collaborate with simulation engineers, drive R&D, mentor junior team members, and work directly with customers to integrate models into production, including onsite customer collaboration and presentations.

Design and implement platform security features, act as security SME for Core Services, perform threat modeling and secure code reviews, support incident response and vulnerability remediation, and provide secure coding standards and developer training.

Build and deploy customer-facing applications that serve physics AI models. Collaborate with data scientists and ML engineers to design E2E solutions, build RESTful APIs and microservices (FastAPI/Python), deploy to cloud using Helm/Kubernetes/Terraform on AWS/Azure, and work onsite with customers to iterate and deliver production tools.

Manage and operationalize research programmes across foundation model and methods work: plan roadmaps, run cadences, track milestones and dependencies, surface and resolve risks, coordinate cross-functional and external partners, support resourcing and research outputs, and communicate progress to stakeholders to enable research teams to focus on science.

As a Principal Research Scientist, you will lead research work-streams, guide junior team members, and collaborate closely with machine learning and simulation engineers to develop AI-driven models for engineering challenges.

Lead development and deployment of high-fidelity multiphase CFD and coupled-physics models for industrial processes. Own geometry cleanup, meshing, solver setup, automation, HPC execution, surrogate modelling, DoE, experimental validation, and customer-facing delivery to translate simulation results into engineering recommendations.

Lead development and validation of high- and low-frequency electromagnetic simulation models for semiconductor, automotive, aerospace, and other industries. Automate simulation pipelines, leverage cloud/HPC for high-fidelity runs, collaborate with data science/ML teams, present results to customers, mentor junior engineers, and travel to customer sites to deploy solutions and validate models with experimental data.

Lead development of predictive maintenance systems using computer vision, integrating multiple data sources to optimize equipment life and availability.