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Luminary

SaaS platform delivering HPC-driven industrial simulations

Geometry/Meshing Engineer

Full-TimeUpdated on 10/20/2026
No salary listed
Expert
PhD
San Mateo, CA, USA
In Person
Software Engineering

About the job

Requirements
  • A Ph.D. in Applied Mathematics, Computational Physics, Aerospace/Mechanical Engineering, or a related discipline.
  • At least five years of software development experience after completing a Ph.D., focused on computational geometry and/or meshing, with a strong track record of delivering customer value.
  • Deep, recognized expertise in computational geometry, meshing, or a related broad domain, particularly experience with 3D complex geometry from realistic, industry-grade applications.
  • Strong experience writing production-level, performant code in C++17 or later.
  • Proficiency in Python.
  • Experience with enterprise-level software development and testing practices.
  • Ability to work directly with customers to deliver successful outcomes while managing risks.
  • Ability to provide mentorship and sponsorship to colleagues toward greater ownership.
  • Ability to work collaboratively in a fast-paced startup environment and communicate clearly.
  • Passion for applying computational physics and artificial intelligence to real-world engineering challenges.
Responsibilities
  • Develop and productize novel computational geometry handling and meshing approaches for physics simulation, including computational fluid dynamics, structural analysis, thermal simulation, and Physics AI workflows, with a focus on automation.
  • Solve significant technical challenges related to geometry ingestion and mesh generation, delivering measurable value to customers.
  • Contribute to the long-term vision for geometry and meshing technology aligned with organizational goals.
  • Identify and resolve significant technical risks to the company's long-term success and provide technical guidance to leadership on roadmapping and key technical trade-offs.
  • Contribute to cross-functional teams focused on customer-centric problem solving.
  • Balance research innovation with practical implementation to enable new product capabilities.
Desired Qualifications
  • Experience with parallel programming using shared memory (OpenMP), MPI for distributed computing, or CUDA for GPUs.

About the company

Luminary Cloud offers a software-as-a-service platform that provides high-performance computing for industrial R&D. It delivers an interactive simulation, visualization, and analysis toolkit that achieves near-supercomputer performance without requiring expensive on-site hardware. Through a subscription model, customers gain ongoing access and updates, avoiding large capital investments in HPC infrastructure. The company focuses on aerospace, automotive, and advanced manufacturing, differentiating itself with strong performance, automation, and cloud scalability backed by expertise in computational physics and cloud computing.

Company Size

51-200

Company Stage

Series B

Total Funding

$187M

Headquarters

Palo Alto, California

Founded

2019

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Simplify's Take

What believers are saying

  • Northrop Grumman and NVIDIA collaborations validate Luminary's product and shorten enterprise sales cycles.
  • SHIFT-Crash and new defense models expand usage from wings into crash, submarines, and pumps.
  • Onshape integration and private-cloud launches broaden distribution and unlock regulated buyers.

What critics are saying

  • Luminary reported about 62 employees in March 2026, down from 87 in 2023.
  • The company still lacks announced hardware wins from Northrop Grumman, despite 2025 collaboration.
  • Defense-heavy positioning creates procurement concentration; one lost program can crater revenue quickly.

What makes Luminary unique

  • Physics AI models predict engineering outputs in seconds across aerospace, automotive, and defense.
  • NVIDIA GeoTransolver and PhysicsNeMo anchor Luminary's technical stack and credibility.
  • Private Cloud supports air-gapped deployments for ITAR-restricted defense and aerospace customers.

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Benefits

  • Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

-6%

1 year growth

-6%

2 year growth

-22%
Luminary
Sep 12th, 2026
Resources | Luminary | Research, News & Events

Articles, research, news, and insights from Luminary on Physics AI and engineering.

Associated Press
Apr 14th, 2026
Luminary launches SHIFT-Crash, first physics AI model predicting full-vehicle crash response in seconds

Luminary has launched SHIFT-Crash, the first Physics AI model that predicts full-vehicle crash response in seconds rather than hours. The model generates spatially resolved stress field predictions from vehicle design parameters, trained on 5,000 crash simulations based on the 2010 Toyota Yaris. Traditional finite element method simulations take 10 to 12 hours per crash test and must restart from scratch for each vehicle programme. SHIFT-Crash uses transfer learning to retain crash physics knowledge across programmes, reducing required simulations from 5,000 for an initial SUV programme to potentially fewer than 300 by the third iteration. The model demonstrates less than 3% root mean square error, enabling engineers to explore design variations earlier in development cycles and accelerate time to market.

Yahoo Finance
Mar 16th, 2026
Luminary adopts NVIDIA GeoTransolver for up to 10x greater accuracy in physics AI

Luminary Cloud has become the first Physics AI platform to adopt NVIDIA's GeoTransolver model architecture for computational fluid dynamics applications, achieving up to 10 times greater prediction accuracy. The technology enables engineering teams to model real-world product performance in seconds rather than weeks. Luminary has retrained its entire SHIFT model portfolio on the new architecture, providing customers with near-simulation-level precision across aerospace, automotive, turbomachinery, marine and space vehicle applications. The models are built on NVIDIA's PhysicsNeMo framework. "Engineering teams have historically had to choose between speed and accuracy," said Suds Menon, Luminary's chief product officer. "By working with NVIDIA and adopting the GeoTransolver architecture across our SHIFT models, we are eliminating that compromise." The advancement addresses a longstanding tradeoff in AI-driven design tools, where faster results typically meant lower accuracy.

Luminary
Mar 16th, 2026
Luminary adopts NVIDIA GeoTransolver AI model architecture, unlocking up to 10x greater accuracy in Physics AI.

Luminary adopts NVIDIA GeoTransolver AI model architecture, unlocking up to 10x greater accuracy in Physics AI. 03.16.2026 San Mateo, CA SAN MATEO, Calif., March 16, 2026 - Luminary Cloud, the leading Physics AI platform, today announced it is the first Physics AI platform to adopt NVIDIA's newest GeoTransolver model for CFD applications, delivering up to 10x greater prediction accuracy for its SHIFT models. This advancement enables engineering teams to model and test real-world product performance with significantly improved precision in seconds rather than weeks, eliminating traditional simulation costs and delays. The company provides engineering teams with ready-to-use Physics AI models built on NVIDIA's PhysicsNeMo framework. SHIFT offers high-precision, pre-trained models across aerospace, automotive, turbomachinery, marine, and space vehicle applications. By retraining its entire SHIFT model portfolio on the new GeoTransolver architecture, Luminary now offers immediate access to higher accuracy and performance. Engineering teams have historically had to choose between speed and accuracy. By working with NVIDIA and adopting the GeoTransolver architecture across its SHIFT models, Luminary Cloud, Inc. is eliminating that compromise. - Suds Menon, Chief Product Officer at Luminary The integration delivers measurable advantages across the SHIFT model portfolio: * External aerodynamics surrogates with maximum accuracy for aerospace, defense, automotive, and industrial sectors * Pre-trained SHIFT models for fluid dynamics, multiphysics, and structural mechanics * Enhanced performance with 45% to 138% speedup on SHIFT-Wing using the newest PhysicsNeMo release "AI-driven simulation is redefining how manufacturing industries design and deliver increasingly complex products," said Tim Costa, VP and general manager of computational engineering at NVIDIA. Customer Application: Sceye Sceye, an aerospace company developing stratospheric platforms for connectivity, earth observation, and climate research, is using Luminary's Physics AI to rapidly evaluate platform performance and refine designs. Leveraging GeoTransolver, Sceye is accelerating design exploration and optimization for its next-generation stratospheric airship. About Luminary Cloud Luminary Cloud is a Physics AI platform for rapid design iteration, exploration, and optimization. Customers span industries from aerospace and automotive to advanced manufacturing, including Northrop Grumman, Otto Aviation, Joby Aviation, Piper Aircraft, and Trek Bikes. For more information, visit www.luminarycloud.com.

Associated Press
Feb 24th, 2026
Luminary launches private cloud to deploy physics AI in secure defense and aerospace environments

Luminary has launched Luminary Private Cloud, an on-premises deployment of its Physics AI platform designed for secure, air-gapped defence and aerospace environments. The system enables high-performance simulation and AI-driven engineering within organisations' own secure perimeters, addressing data sovereignty and classified workflow requirements. The platform delivers the same capabilities as Luminary's cloud-hosted service, including AI-driven simulation, model training and inference, whilst operating entirely within restricted environments. It builds on existing ITAR-compliant deployment options and SOC 2 Type 2 and ISO/IEC 27001:2022 certifications. The launch reflects growing demand for deployable AI solutions in regulated industries where public cloud infrastructure is prohibited. The system maintains consistency with Luminary's SaaS platform and enables potential future hybrid deployments between private and public infrastructure.