Jobs at PhysicsX

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.

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.

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.

Develop and own high-fidelity computational plasma models for semiconductor etching and deposition, validate simulations against process data, collaborate with Data Scientists/ML engineers, work onsite with customers to scope challenges, integrate simulation into AI workflows, lead projects and mentor juniors, and travel globally to deliver solutions.

The Content & Communications Strategist will create compelling narratives for various channels, manage an editorial calendar, and collaborate across departments to enhance brand storytelling and engagement.

Own the product organisations operational rhythm: run quarterly roadmap and fortnightly sprint governance, maintain Linear as single source of truth, manage cross-team dependencies and inbound triage, improve processes and automation, keep operational documentation, track throughput and support capacity planning to ensure delivery across multiple product teams.

Lead the Research team in developing scalable machine learning solutions, mentoring junior engineers, optimizing model training, and collaborating on real-world engineering problems.

Develop machine learning models for real-world physics problems, optimize model performance, implement distributed training, and mentor less experienced colleagues.

Lead deployment of production ML systems for physics-based engineering: design scalable training/inference pipelines, work with 3D point-clouds and mesh data, collaborate with customers onsite, mentor engineers, define architecture and success metrics, and deliver robust cloud and on-prem ML solutions.

The Senior CFD Engineer will develop complex multiphysics models, validate DEM models, automate simulation workflows, mentor juniors, and engage with customers globally to solve engineering challenges.

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

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.