--- title: 'CFD Engineer at PhysicsX' canonical: 'https://feeny.ai/job/cfd-engineer-physicsx-singapore-4fc35cfjnfyh' type: 'job' last_seen: '2026-09-09' --- # CFD Engineer at PhysicsX - **Company:** PhysicsX - **Location:** Singapore - **Posted:** 2026-08-07 - **Last confirmed live:** 2026-09-09 - **Apply:** https://job-boards.eu.greenhouse.io/physicsx/jobs/4948904101 ## Job description ## 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 — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. Who We’re Looking For As a CFD Engineer (Delivery), you are a problem solver and a builder, who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly with customers (often directly on-site) to build CAE models that are integrated into AI-tools that are both useful and used. We're building our Singapore presence from the ground up. This is a rare opportunity to join at the founding stage of a regional team, with the autonomy to help define what this team becomes. You bring a growing foundation in fluid mechanics, heat transfer, and multiphase modelling, with the ability to apply core engineering principles to real-world problems under guidance from more senior colleagues. You have working knowledge of at least one of Star-CCM+, OpenFOAM, or Fluent, and are comfortable using built-in automation features to support scalable workflows. Exposure to parametric CAD modelling (NX or CATIA) and coding in Python/Java - or a demonstrated ability to pick up new tools and languages quickly - is an advantage. With 1-3 years of industry experience (post-Masters or PhD) in a commercial, non-research environment, you're building your independence. You're comfortable setting up CFD simulations for moderately complex cases with some support, developing your ability to interpret results, and building the engineering judgement that comes from hands-on experience. This Role In this role, you'll work alongside our Data Scientists, Machine Learning Engineers, and (with support) our customers to help define and solve engineering challenges. You'll contribute to delivering high-fidelity simulations by: - Building models from geometry clean-up and meshing through to simulating and post-processing, for simple to moderately complex cases, with guidance from senior engineers on the more difficult aspects. - Adapting and using parametric CAD models (NX or CATIA), and beginning to contribute to simulation pipeline automation for design optimisation and DoE studies. - Supporting customer-facing work by helping prepare and present results clearly, under the direction of more senior team members, while building toward doing this independently. - Working at the intersection of CAE and Data Science to help generate simulation datasets for training Machine/Deep Learning models, and developing your understanding of how data sampling choices affect model accuracy and cost. - Using Flux (our cloud platform) and on-premise HPC resources to run simulations, and learning how to apply smarter meshing and setup choices to improve performance. - Learning and applying engineering best practices, and helping adapt CFD model setups and outputs to support Deep Learning surrogate development. - Contributing to a culture of collaboration and shared learning within the Simulation Engineering guild - for example, sharing what you learn, flagging gaps in documentation, or (at L2) starting to support onboarding of newer engineers. - Travelling occasionally (Europe, Asia, Oceania) to support customer engagements alongside senior colleagues, with the expectation that this will increase as you build independence. 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. ## About PhysicsX ## Company Overview - **One-liner**: PhysicsX builds an AI-native software stack for physics simulation and engineering design, enabling advanced industries to accelerate innovation by orders of magnitude. - **Entity Type**: Private (Series C) - **Headquarters**: London, United Kingdom - **Founded**: 2019 - **Founders**: Jacomo Corbo (CEO & Co-Founder) and a Co-Founder & Chairman ## Core Business - **Primary industries**: Aerospace & Defense, Automotive, Semiconductors, Materials, Energy & Renewables - **Target customers**: Large industrial organizations (B2B Enterprise) – engineers and teams designing and operating complex physical systems - **Mission**: Empower industrial organizations to build beyond human imagination and address the defining challenges of our time, with a focus on climate and human health impact ## Products & Services - **PhysicsX Platform** (SaaS + embedded engineering): An AI-native software stack that unifies simulation, physics AI, data, and engineering applications. Integrates with existing toolchains (CAD, CAE, PLM) and accelerates simulation by orders of magnitude, enabling engineers to explore larger design spaces and move from concept to validated design in days. ## Market Standing - **Valuation**: Approximately $2.4B (as of Series C in August 2026) - **Key Metric**: Total funding ~$487M (including $300M Series C, $135M Series B, $32M Series A, $20M from NVentures). Revenue is generating but not publicly disclosed (LinkedIn estimates ~$1M, but company is early-stage revenue generating). - **Notable Investors/Partners**: Atomico (led Series B), General Catalyst (led Series A), NVentures (NVIDIA’s venture arm), NVIDIA (strategic partner), Siemens (collaboration on data center power infrastructure) - **Growth Signals**: - Series C oversubscribed $300M at $2.4B valuation (Aug 2026) - Headcount growth of 71% YoY (LinkedIn: 226 employees; PitchBook: 350 employees post-C) - Forward-deployed engineers embedded in customer programs - Open standards for physics AI powered by NVIDIA (March 2026) ## Competitive Advantages - **True AI-native platform**: Physics AI is built as a core primitive, not bolted onto legacy tooling. Uses advanced models like Fourier Neural Operators to simulate physics at speeds unattainable with traditional CFD/FEA. - **Embedded deployment model**: Forward-deployed engineers work alongside customers on live problems, ensuring measurable outcomes and deep domain integration. - **Focus on hardest problems**: Targets extreme complexity (aerospace, semiconductors, climate tech) where speed of development is critical and margins for error are zero. - **Strategic partnerships**: Deep collaboration with NVIDIA (compute, open standards) and Siemens (infrastructure AI). ## Strategic Focus - Continue scaling the platform across multiple industrial verticals, with emphasis on the climate transition (energy, materials efficiency) and human health (medical devices, supply chain). - Expand the "Large Physics Models" research program and open standards initiatives. - Grow the global team (currently 350+ across UK and US) with strong emphasis on research, product engineering, and forward deployment. ## Why Work Here - **Culture**: Grounded visionaries, moving fast with trust and ambition. Values include "we make stuff happen" and "we form a community in which people can grow." - **Work environment**: Hybrid (2-3 days in office per week); offices in London (Shoreditch) and New York (Downtown Manhattan). Visa sponsorship and relocation support available. - **Benefits**: Generous pension contributions, health insurance, enhanced parental support, development opportunities. - **Engineering culture**: Work on the hardest problems in industry – physics, AI, and engineering collide. Small, high-autonomy teams. Interview process includes pairing and in-person final rounds. - **Diversity**: Committed to equal opportunities; strongly encourages underrepresented groups to apply. ## Sources 1. [PhysicsX.ai](https://www.physicsx.ai/) – company website 2. [PhysicsX About](https://www.physicsx.ai/about) – mission, team, challenge 3. [PhysicsX Careers](https://www.physicsx.ai/careers) – culture, benefits, interview process 4. [LinkedIn](https://uk.linkedin.com/company/physicsx) – employee count, funding, headcount growth 5. [PitchBook](https://pitchbook.com/profiles/company/529644-70) – valuation, Series C, founding year ## Other roles at PhysicsX - [CFD Engineer](https://feeny.ai/job/cfd-engineer-physicsx-new-york-ed2z3r3afh4y) — New York, NY - [Delivery Operations Manager](https://feeny.ai/job/delivery-operations-manager-physicsx-london-6nb5k6xmx8fw) — London, United Kingdom - [Forward Deployed Software Engineer](https://feeny.ai/job/forward-deployed-software-engineer-physicsx-london-ctmsk9sjcj5a) — London, United Kingdom - [Staff Backend Software Engineer - GO & Python](https://feeny.ai/job/staff-backend-software-engineer-go-python-physicsx-london-jya69fmtw4c3) — London, United Kingdom - [Strategy & Programs Manager](https://feeny.ai/job/strategy-programs-manager-physicsx-london-gn01bh125dtg) — London, United Kingdom - [Deployment Strategist - Aerospace & Defense](https://feeny.ai/job/deployment-strategist-aerospace-defense-physicsx-new-york-navkewnrbqwc) — New York, NY - [Senior Simulation Engineer - Electromagnetics Specialist](https://feeny.ai/job/senior-simulation-engineer-electromagnetics-specialist-physicsx-new-york-q1a4azp2whvc) — New York, NY - [Senior Machine Learning Infrastructure Engineer, Research](https://feeny.ai/job/senior-machine-learning-infrastructure-engineer-research-physicsx-singapore-mswd3dgrk4na) — Singapore - [Senior Financial Accountant](https://feeny.ai/job/senior-financial-accountant-physicsx-london-z4v89d624rkj) — London, United Kingdom - [Finance Assistant](https://feeny.ai/job/finance-assistant-physicsx-london-tsawqpv63dvb) — London, United Kingdom