Physics Applications - Researcher

Vinci • Palo Alto, CA

5d

About The Position

Vinci is building operator intelligence infrastructure for hardware programs, using a unified foundation model for physics applications. The company is expanding its capabilities from steady-state solutions of partial differential equations into transient modeling of interactions, deformation, and dynamics. The role focuses on developing and delivering production applications using the Vinci framework, with an emphasis on customer value, iterative development, and hardening features for deployment.

The researcher will explore classical and learned temporal propagation schemas, use existing data-generation infrastructure to produce and curate training and verification samples, and work closely with customers and a multidisciplinary team. The role includes carrying early prototypes through iteration and production hardening, contributing to core model infrastructure, and meeting software design, testing, and validation standards.

Requirements

• Published work leveraging or building a simulation practice.
• At least 4 years of experience with an MS/MSc, or at least 2 years with a PhD.
• At least 2 years using or building physics simulators, such as FEM, FEA, Molecular Dynamics, or FDTD.
• Experience with applied machine-learning approaches, including computer vision, GraphNN, or transformer architectures.
• Working knowledge of modern machine-learning fundamentals, including backpropagation, loss functions, generators, embeddings, and transformer models.
• Experience with modern machine-learning practices and tools such as PyTorch, NumPy, and CUDA, as well as training and evaluation practices.
• Contribution to a production data-processing system.
• Software engineering fundamentals and ability to meet software design standards for production code.
• Ability to leverage existing infrastructure and close implementation gaps as needed.

Nice To Haves

• Applied machine learning to meshing geometry or accelerating FEM or DFT simulations.
• Experience taking an early-stage prototype into a production environment at a startup or national laboratory.
• Experience leveraging simulation for design or data-generation purposes.

Responsibilities

• Experiment with classical and learned temporal propagation schemas.
• Use existing data-generation infrastructure to generate and curate training and verification samples.
• Develop new application utility through modest iterative steps and work with customers to harden features.
• Collaborate with physicists, AI researchers, software engineers, and computational geometry experts.
• Carry early prototypes through iteration and hardening to customer use.
• Leverage pre-existing infrastructure and contribute to production-ready software.
• Follow software design standards and maintain strong CI, regression testing, and validation practices.
• Contribute to the evolution of core model infrastructure.

Benefits

• Opportunity for technical and professional growth at an early-stage startup.
• Opportunity to own and architect large pieces of the system.
• Opportunity to work on greenfield expansion of the company's core capabilities.
• Small, friendly, and accessible team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level