Luminary Cloud helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.

What you'll do

• Pioneer Physics AI adoption by leading the end-to-end integration of our platform for customers ranging from hyper-growth startups to the Fortune 100.
• Work closely with customers to identify high-impact opportunities and design bespoke solutions that adapt the platform to their specific needs.
• Opportunity to travel to customer sites to provide hands-on support and work side-by-side to ensure successful implementation.
• Provide expert technical guidance and support throughout the customer lifecycle, from initial deployment to ongoing optimization.
• Collaborate with cross-functional teams by translating customer needs and insights into actionable feedback for our product and research teams, directly shaping the next generation of Physics AI.

What you bring

• Passionate about engaging customers and traveling onsite. CAE industrial experience is highly valued.
• Proficiency in Python for scripting and automation, familiarity with a primary deep learning framework (e.g. PyTorch), and API/SDK workflows.
• Hands-on experience with cloud platforms, containerization, and version control systems.
• Tech-savvy mindset with enthusiasm for cloud computing and advanced simulation technologies.
• Self-starter mentality with the ability to work independently and drive results.
• Exceptional communication skills, particularly when engaging with technical audiences.

Qualifications

• An engineering or physics background (e.g., Mechanical, Aerospace) with demonstrated expertise in data science and Physics AI.
• Experience with CFD software, simulation workflows, or scientific computing.
• Familiarity with ML operations and physics-informed AI/ML models/frameworks (e.g. PhysicsNeMo).