Top Tech Jobs & Startup Jobs in London

Own the roadmap for PhysicsX’s Cloud Developer Environment and release engineering products while incubating an agentic software factory. Lead discovery, prioritization, secure software delivery, disconnected deployments, staged releases, rollback, installation experiences, and measurement of delivery quality and speed. Partner with engineering and deployment teams to productize developer tooling for regulated, customer-operated environments.

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.

Owns the full lifecycle of task-based, in-platform technical documentation and how-to guides, from scoping and research through validation, publication, release updates, testing, and maintenance. Partners with curriculum leads, subject matter experts, Product, Engineering, and GTM leadership to ensure guides accurately support machine learning and simulation workflows. Maintains documentation backlogs, validates technical content independently, and keeps guidance current with platform releases.

Design, provision, and operate reliable shared infrastructure across AWS, GCP, Azure, and on-premises environments. Manage Kubernetes clusters, multi-tenancy, secrets, GPU workloads, networking, service meshes, and infrastructure as code using Terraform and Crossplane. Develop operators, establish reliability targets, respond to incidents, and partner with security and platform teams on governance and compliance.

Lead research on generative models and learned representations for 3D engineering geometry. Design and train models using representations, latent spaces, and physics-based objectives; evaluate outputs with production numerical solvers; formulate engineering problems with ML and simulation teams; guide research direction, mentor colleagues, and publish findings. The role focuses on geometric deep learning, generative modeling, neural fields, and coupling geometry generation with physical objectives.

Own PhysicsX’s global events strategy and calendar, manage external conference programs, and produce executive, customer, research, talent, and launch experiences end-to-end. Responsibilities include budgeting, vendor and venue management, speaker coordination, event logistics, stakeholder collaboration, onsite execution, post-event analysis, and ROI reporting. The role builds scalable event processes and playbooks while ensuring experiences support commercial, research, talent, and brand objectives.

Own and evolve HPC infrastructure supporting CPU- and GPU-intensive engineering simulations, including cluster administration, scheduling, performance tuning, and capacity planning. Provide escalated IT support, administer identity and access controls, support developer tooling and cloud environments, and implement zero-trust and compliance practices. The role also requires strong networking, automation, scripting, troubleshooting, mentoring, and process-building skills in a scale-up environment.

PhysicsX invites candidates to join its talent community for future opportunities across research, data science, machine learning engineering, product, and delivery. The company develops AI-driven simulation software for engineering and manufacturing in advanced industries including aerospace, energy, semiconductors, materials, and automotive. Applications are reviewed for potential future roles, with no active vacancy or immediate progression guaranteed.

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.

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.