Member of Technical Staff - Software Engineer
Vinci4dAbout the role
About Us 🚀
We're building an AI assistant for hardware designers. Our mission is to enable millions of hardware designers and engineers to iterate through designs 1000x faster.
We are building our geometry + physics driven foundation model for each class of part design.
We are looking for people who love to build new products to help us improve our MVP.
Your Responsibilities
You’ll be a force multiplier for our team and will design and develop the pipelines and tools that make our product a product. This includes accelerating our development by developing the system that enables our code to go from development to deployment. You’ll also orchestrate how data flows throughout the deployed product. Specific tasks include:
Develop key features to improve our product including: making it more scalable, developing improving APIs to enable more complex engineering workflows
Set up and integrate LLM or VLM infrastructure
Set up an MLOps framework for training deep learning architectures for geometry and physics data
Assist in the strategy, planning the product roadmap, and prioritize the development in partnership with early customers and design partners
Build and ship critical product features
Learn a lot while building products that engineers will love. Also learn about entrepreneurship!
Qualifications
6+ years of experience developing and shipping features in the space of high performance computing.
Proficiency in C++, Python, or any other language necessary for setting up a system. Tools like grpc, protocol buffers, Docker, Kubernetes, Bazel (or your favorite language agnostic build system)
Proficiency in using cloud compute be it for data generation, scraping, and enabling data science teams to train models with MLOps is a plus
CUDA experience would be amazing but not required
Frontend experience is a plus
Startup experience is a strong advantage.
You’re a great fit for this role if you
Are excited about entrepreneurship, taking things from 0 to 1,
Have a continuous learning mindset.
Are interested in building a geometry and physics based model for a vast variety of design problems (e.g. heat dissipation system for chips to landing gears)!
Thrive when you have autonomy and ownership over your work
Responsibilities
- Design and develop pipelines and tools for product development
- Develop key features to improve product scalability and APIs
- Set up and integrate LLM or VLM infrastructure
- Establish MLOps framework for training deep learning architectures
- Assist in strategy and product roadmap planning
- Build and ship critical product features
Qualifications
- 6+ years of experience in high performance computing
- Proficiency in C++, Python, or other necessary languages
- Experience with tools like grpc, Docker, Kubernetes
- Cloud compute experience for data generation and MLOps
- CUDA experience is a plus
- Frontend experience is a plus
- Startup experience is a strong advantage
Skills mentioned
About Vinci4d
Vinci is a frontier lab building the foundation model for the physical world. The company is developing deterministic, solver-grounded systems that make physics continuously computable, shifting engineering from episodic simulation to continuous physics infrastructure. Already deployed inside production engineering workflows and running on flagship programs, Vinci operates directly on native design and manufacturing geometry to enable high-fidelity physics reasoning without the traditional burden of manual setup, meshing, and specialist-only access. Rather than functioning as a faster point tool, Vinci changes the operating model of engineering by making physics more available, more repeatable, and more actionable across the organization. Its systems support design, verification, manufacturing, and reliability decisions, helping teams evaluate more scenarios, surface physical risk earlier, and improve engineering leverage without scaling specialist simulation teams linearly. Vinci’s broader aim is to make physics a shared reasoning layer for designing, building, and operating the physical world.