Physics Applications - Researcher (Senior)

Vinci4D.ai; Palo Alto (CA); On-site; USD 190,000 - 260,000; Full time

Job summary

Vinci4D.ai, based in Palo Alto, is seeking a talented individual to develop the operator intelligence infrastructure for modern hardware programs. The role involves leveraging simulation practices and machine learning to deliver value to Tier-1 semiconductor and hardware customers.

The successful candidate will have a strong background in physics simulations and software engineering, working closely with a team of experts. Compensation ranges from $190K to $260K, depending on experience.

Qualifications

• Published work leveraging or building a simulation practice.
• Experience using or building physics simulators like FEM and FEA.
• Applied ML approaches including Computer Vision and Transformer Architectures.

Responsibilities

• Leverage the Vinci framework for novel applications.
• Collaborate with Physicists and AI researchers on prototypes.
• Iterate features based on customer feedback.

Skills

Simulation practice experience

Physics simulation

Machine learning

Modern ML practices (PyTorch, Numpy, Cuda)

Software engineering fundamentals

Education

MS/MSc with 4+ years experience or PhD with 2+ years experience

Tools

Python

PyTorch

Numpy

Cuda

Job description

The Mission

At Vinci, we are building the operator intelligence infrastructure that modern hardware programs rely on daily. We have already proven that a single foundation model works out of the box across physics on realistic production workloads.

• Trained on PetaBytes of structured physics data
• Running billion-voxel inference in production
• Tier-1 semiconductor and hardware customers
• Operating across multiple physical scales and operator regimes
• Increase simulation throughput by two orders of magnitude
• Expand simulation capabilities to maximize utility and domain coverage
• Support global, multi-entity deployment across Tier-1 ecosystems
• Our ambition is to become the default operator intelligence layer that hardware companies run on

Solving Across Space and Time

Our proven unified model architecture allows users to rapidly obtain steady state solutions of various partial differential equations. We are expanding this capability into the transient domain, modeling interactions, deformation and dynamics. These are promising applications where Vinci’s approach can not only reduce the compute load but also achieve greater accuracy.

What You Will Do

Your north star will be production and delivering value to our customers.

In this role you will leverage the Vinci framework to work on a variety of novel applications. Experiment with temporal propagation schemas, both in the classical and learned sense. You will use pre-existing data generation infrastructure to generate and curate training and verification samples. You will take modest iterative steps to prove out new utility and iterate hand in hand with customers to harden features.

You will work with Physicists, AI researchers, Software Engineers and Computational Geometry experts. You will work with a team to carry early prototypes through iteration and hardening all the way to customer use.

What We’re Looking For

Qualifications:

• Have published work leveraging or building a simulation practice.
• MS/MSc with 4+ years experience or PhD with 2+ years experience
• 2+ years using or building physics simulators (FEM, FEA, Molecular Dynamics, FDTD)
• Applied machine learning approaches (Computer Vision, GraphNN, Transformer Architectures)
• Working knowledge of modern ML basics (back prop, loss functions, generators, embeddings, transformer models)
• Experience with some modern ML practices (PyTorch, Numpy, Cuda, Training & Evaluation practices)
• Have contributed to a production data processing system.
• Have applied ML to meshing geometry or accelerating FEM or DFT simulations
• Experience moving from early prototype to production at a startup or national lab
• Have leveraged simulation for design or data generation purposes

Engineering Expectations

• Software engineering fundamentals
• Comfortable meeting software design standards to get code into production
• Capable of leveraging pre-existing infrastructure and “closing the gap” on occasion
• Strong CI, regression testing, and validation discipline
• Comfort evolving core model infrastructure

Reason to Join

Join a rare early-stage startup that has successfully moved a foundational product from research to real-world, production environments, already serving Tier-1 semiconductor and hardware customers.

Compensation Range

$190K - $260K