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About 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.

Responsibilities

Extend and operate the Data Factory infrastructure that orchestrates thousands of CFD simulations per day on cloud compute
Design and operate job scheduling systems that maximize throughput while handling failures gracefully
Build monitoring and alerting to detect simulation failures, convergence issues, and resource bottlenecks early
Build high-performance data pipelines that move simulation outputs from solver results to ML-ready training data
Implement geometry preprocessing workflows (mesh preparation, morphing, watertightness validation)
Design and operate post-processing pipelines: surface decimation, field interpolation, format conversion
Optimize I/O performance for large mesh datasets
Implement comprehensive validation checks at every pipeline stage: solver convergence, physical field bounds, post-processing fidelity
Build systems that capture and quarantine bad data before they reach training pipelines
Track and report data quality metrics across the entire Data Factory
Work towards full provenance: training samples should be traceable back to their source geometry and simulation configuration
Deliver validated datasets to downstream ML training infrastructure in formats optimized for efficient data loading
Design data versioning and cataloging systems that support reproducible training runs
Work closely with ML Infrastructure Engineers to ensure smooth handoff between data production and model training
Support multi-dataset training workflows

Requirements

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.
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
Understanding of CFD fundamentals, enough to interpret solver outputs and validation metrics
Experience with 3D geometry pipelines (mesh decimation, field interpolation)
Familiarity with ML data loading patterns and how training systems consume data

Skills

Python
SLURM
Kubernetes
Temporal
Linux
networking
storage systems
performance debugging
CoreWeave
CFD
FEA
StarCCM+
OpenFOAM
ANSYS
PyVista
HDF5
VTK
NetCDF
Zarr

Location

Shoreditch office

Work Type

Hybrid

Experience Level

5+ years of experience in data engineering, HPC engineering, or simulation infrastructure.

Benefits

Equity options
10% employer pension contribution
Free office lunches
Enhanced parental leave
YellowNest nursery scheme
25 days of Annual Leave (+ Public Holidays)
Private medical insurance
Wellhub Subscription
Eye tests
Personal development
Employee Assistance Programme (EAP)
Bike2Work scheme
Season ticket loan
Octopus EV salary sacrifice

About the Company

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 — empowering engineers to push the boundaries of possibility.
Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

Equal Opportunity

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.