
PhysicsX is a deeptech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulationβ¦

PhysicsX is a deeptech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulationβ¦
What they do: AI-driven, physics-grounded real-time multiphysics simulation software for engineering and manufacturing
Headquarters: London, United Kingdom
Recent funding: $135M Series B (June 2025) after a $32M Series A (Nov 2023)
Customers / industries: Aerospace & Defense, Automotive, Semiconductors, Energy, Materials
Multiphyics simulation and engineering workflows (design, manufacturing, operations) for advanced industries
Software Development
32000000
Participants included Standard Investments, NGP, Radius Capital and Henry Kravis
135000000
Participants included Temasek, Siemens, Applied Materials, July Fund and continued support from existing investors
155000000
Dealroom reporting of an extension raising over β¬133M (~$155M) with reported participation from NVentures
βSignificant strategic investor participation including Atomico, Temasek, Siemens, Applied Materials and NVenturesβ
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About Us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations β empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
The Role
The Senior Simulation Data Engineer will extend and operate the infrastructure that powers our research Data Factory. You will be responsible for the end-to-end pipeline: from geometry preparation and simulation orchestration through validation, post-processing, and delivery to downstream ML training systems, using PhysicsX platform orchestration services where synergies exist.
This role sits at the intersection of HPC engineering and data engineering. You will orchestrate long-running CFD simulations at scale, build robust data pipelines, and ensure that every simulation we produce meets rigorous quality standards.
Team Context
In this role, you will be vertically embedded in Research , working daily with:
You will have end-to-end responsibilities over the Data Factory, with the autonomy to make architectural decisions and the responsibility to keep data flowing reliably.
Horizontally, you will be part of an infrastructure engineering group responsible for infrastructure across the company.
What you will do
Simulation Orchestration
Data Pipeline Engineering
Data Quality and Validation
Integration and Delivery
What you bring to the table
Ideally
What We Offer
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
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Ability to scope and effectively deliver projects, prioritising activity as needed.
Problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
Excellent collaboration and communication skills, especially in a research setting. You can translate "the model isn't converging" into infrastructure hypotheses and solutions, and can bridge technical abstractions with implementations.
5+ years of experience in data engineering, HPC engineering, or simulation infrastructure.
Strong experience with orchestration systems: SLURM, Kubernetes, Temporal
Production data pipeline experience: you've built and operated pipelines that process large volumes of data reliably
Proficiency in Python for pipeline development and automation
Systems engineering fundamentals: Linux, networking, storage systems, performance debugging
Experience with cloud infrastructure; ****ideally CoreWeave or similar GPU/HPC-focused clouds
Background in HPC for simulation engineering: experience with CFD, FEA, or similar computational workflows (StarCCM+, OpenFOAM, ANSYS, etc.)
Experience with geometry processing: mesh manipulation, CAD formats, PyVista
Familiarity with scientific data formats: HDF5, VTK, NetCDF, Zarr
Data quality engineering experience: validation frameworks, anomaly detection, data observability