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PhysicsX is a deep-tech company building an AI-driven simulation software stack for engineering and manufacturing across aerospace, defense, materials, energy, semiconductors, and automotive. The company accelerates hardware innovation by enabling high-fidelity, multi-physics simulation through AI inference across the engineering lifecycle.
As Principal CFD Engineer (Delivery), you will be a founding member of PhysicsX's Singapore regional team, with autonomy to help shape the team's direction. You'll work at the intersection of computational fluid dynamics, machine learning, and customer delivery, solving complex engineering challenges across multiple industries.
Key responsibilities include:
- Independently building complex multi-physics CFD models from geometry cleanup and meshing through simulation and post-processing, integrating experimental data for validation
- Creating robust parametric CAD models (NX or CATIA) coupled with simulation pipeline automation for design optimization and design-of-experiments studies
- Partnering directly with customers (often on-site) to address their most complex engineering challenges, presenting results clearly and recommending actionable next steps
- Generating high-quality simulation datasets for training machine learning models, using data sampling techniques to efficiently capture design space and reduce computational cost
- Leveraging Flux (the company's cloud platform) and on-premise HPC resources to accelerate high-fidelity modeling
- Continuously improving engineering best practices and adapting CFD outputs to support deep learning surrogate development
- Mentoring junior colleagues and contributing to a collaborative culture
- Traveling globally (North America, Europe, Asia, Oceania) up to 2–3 weeks per quarter for on-site customer work
You bring 5–7 years of post-Masters/PhD commercial (non-research) CFD experience with deep expertise in fluid mechanics, heat transfer, and multiphase modeling. You are highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent, with strong ability to automate these tools for scalable optimization workflows. Experience with parametric CAD modeling and Python/Java coding is expected or quickly learnable. You are confident setting up CFD simulations independently, interpreting complex results with engineering judgment, and making informed decisions under tight deadlines.
The role offers growth opportunities as either an individual contributor or team lead as the regional presence expands.
