Senior Simulation Data Engineer

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. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. We are recruiting for multiple roles; please apply for the role that best aligns with your skillset and career goals.

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.
• Collaborate with ML Infrastructure Engineers to ensure smooth handoff between data production and model training.
• Support multi-dataset training workflows.
• Maintain end-to-end ownership of Data Factory with autonomy to make architectural decisions and ensure reliable data flow.

Qualifications

• 5+ years of experience in data engineering, HPC engineering, or simulation infrastructure.
• Strong experience with orchestration systems: SLURM, Kubernetes, Temporal.
• Production data pipeline experience: 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.

What We Offer

• Equity options – share meaningfully in the company you’re helping to build.
• 10% employer pension contribution – investing in your future.
• Free office lunches.
• Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave.
• YellowNest nursery scheme – support for childcare costs.
• 25 days of Annual Leave (plus public holidays).
• Private medical insurance – 100% employee cover.
• Wellhub Subscription – access to gyms, classes and wellness apps.
• Eye tests.
• Personal development – dedicated support for learning and growth.
• Employee Assistance Programme (EAP) – confidential wellbeing support.
• Bike2Work scheme and Season ticket loan.
• Octopus EV salary sacrifice – sustainable commuting option.

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 monitoring equality policies and UK employment legislation; the information is confidential and used only in aggregate form.