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Salary
≈ $35k – $83k per year (Estimated)
Location
In office (Singapore)

Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Oct 29, 2026. PhysicsX scores A on the Alion truth index.

Overview
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Profile match
PhysicsX is a deep technology company that develops artificial intelligence and simulation software to accelerate engineering and advanced manufacturing. Founded by former Formula One engineers and computer scientists, the organization uses physics-informed AI and deep learning to optimize complex designs in fields like aerospace, automotive, and renewable energy. By replacing traditional, time-intensive physics simulations with real-time machine learning models, it enables companies to innovate faster and dramatically improve performance.

About us

Re-architecting Engineering for the Age of Intelligence

PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.

Who We’re Looking For

As a Senior Simulation 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.

You bring deep expertise in metallurgical, chemical, heat transfer, and multiphase modelling, with a solid ability to apply fundamental knowledge to real-world phenomena across a wide range of engineering applications. Highly proficient in at least one of Abaqus, ANSYS Mechanical/Fluent, and adept at automating these tools to create scalable optimisation workflows that drive impactful results. Experience in parametric CAD modelling (NX, FreeCAD or CATIA) and coding in Python/Java, (or the ability to quickly learn programming languages).

With industrial / line-side / manufacturing process experience in a commercial, non-research environment, you're ready to hit the ground running. You're confident setting up simulations independently, interpreting complex results with depth, and making informed decisions based on solid engineering judgement.

Technical Competencies

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.

  • Deep proficiency in thermal and heat-transfer simulation across platforms (Abaqus, ANSYS Mechanical/Fluent, COMSOL, or equivalent), including conduction, convection, radiation, and transient heat-transfer modelling with temperature-dependent material properties
  • Deep proficiency in coupling thermal, chemical, fluid, diffusion, and electrostatic phenomena
  • Strong grasp of numerical methods and solver fundamentals - discretisation schemes, convergence behaviour, stability, mesh sensitivity, and the judgement to diagnose non-physical results rather than accept solver output at face value
  • Instrumentation design and real-world data collection - instrumenting physical processes (sensors, test rigs, in-situ measurement) to generate validation data for processes that have no existing simulation capability
  • Hands-on, real-world experience on the shop floor with manufacturing plants, industrial engineering processes, and/or repair operations - not simply desk-based familiarity
  • Awareness of qualified-process and regulatory constraints - understanding that model outputs must respect qualified parameter windows, and distinguishing optimisation within a qualified window from changes that trigger requalification
  • Customer-facing delivery - partnering with client process owners to scope and address complex repair challenges; communicating results clearly and balancing accuracy with efficiency under commercial deadlines

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 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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