Careers at Vinci

About Us Vinci combines a foundation model for physics with GPU-native solvers to deliver unprecedented simulation speed and accuracy. There’s no meshing, no approximations, and customer data is not required to train the model: it simply works out of the box. Vinci enables engineers to run thousands of simulations seamlessly, transforming how complex physical systems are designed and optimized. Our teams rely on high-performance compute, secure networking, and cloud integrations to accelerate development. We’re looking for a pragmatic full-stack engineer who can span customer-facing UIs, backend services, and native C++ integrations — someone who ships features end-to-end and takes ownership of how customers consume them. Role Summary Hands-on full-stack role. You’ll build and operate Python/gRPC services that expose capabilities from C++ engines, make small–medium UI changes to customer and internal apps, and own the application work required to make features consumable by customers. The ideal candidate is comfortable working across the stack, fluent in shipping production services, and motivated to make the product easier and safer for customers to use. What You’ll Do Design, implement, and operate Python-based microservices and gRPC APIs that expose native C++ engines and simulation/inference pipelines. Implement small-to-medium UI changes and work with product/UX on customer-facing React apps (TypeScript/JS, HTML/CSS) — from bug fixes to adding new pages or controls. Implement application logic end-to-end: request validation, job orchestration, retries/idempotency, transactional correctness, and SDKs/APIs for customers. Help design and operate distributed systems: job partitioning, backpressure, retries, observability, and autoscaling for services that coordinate native compute. Debug and profile across the stack — from frontend performance and network requests to Python runtime and native C++ hotspots. Build CI/CD pipelines and automated tests (unit, integration, e2e) that cover backend, frontend, and native components. Participate in on-call rotations, incident response, and post-mortems; maintain runbooks and operational dashboards. Collaborate with product, QA, infra, and customer success to ensure features are usable, secure, and well documented. Mentor teammates and contribute to code reviews and engineering best practices. Required Qualifications 5+ years professional software engineering experience building backend or full-stack systems. Strong experience with Python service development (sync/async) and building/consuming gRPC /protobuf APIs. Practical PostgreSQL experience: schema design, safe migrations, query tuning, indexing, and optimizing queries for production workloads. Practical experience with React (or equivalent modern frontend framework), TypeScript/JavaScript, HTML/CSS, and shipping UI changes to production. Good knowledge of concurrency and multi-threaded programming, and how to reason about concurrency across language boundaries. Experience working in large codebases with good engineering practices (testing, CI/CD, code review, documentation). Strong communication skills and an appetite for taking end-to-end ownership of customer-facing features. Preferred / Bonus Skills Experience exposing native C++ features to Python (pybind11, CFFI). Familiarity with EDA/layout or domain file formats (OAS, GDS, ECXML, STL, STEP). Experience distributing compute with MPI, task queues, or job schedulers; knowledge of Kubernetes, Slurm, or HPC schedulers. GPU acceleration experience (CUDA/ROCm) or integrating GPU-accelerated C++ libraries. Knowledge of binary serialization (protobuf, FlatBuffers), zero-copy techniques, and high-performance I/O (io_uring). Experience with observability tooling (Prometheus, OpenTelemetry, structured logging, tracing). Experience with authentication patterns (OAuth2, JWT, mTLS) and secure frontend/backend interactions. Knowledge of Linux internals and debugging: processes, threads, signals, memory, and common syscalls. What We Value Engineers who ship customer-usable features and take responsibility for operational quality. Pragmatism: delivering maintainable, well-tested solutions that meet product and performance goals. Systems curiosity: willingness to dig into low-level behavior to solve real problems. Collaboration: clear code reviews, documentation, and mentorship. Compensation & Benefits Competitive salary, equity, health benefits, flexible time off, and remote-friendly policies. Final compensation depends on experience and location.

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

About us 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 We are scaling deployment at industrial magnitude: 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. To get there, we need the backend and infrastructure that lets our research move to production reliably, repeatably, and at scale. Building the Backbone Our unified model architecture delivers steady-state and transient solutions to partial differential equations at production scale. None of that reaches a customer without robust infrastructure underneath it: reproducible builds, automated pipelines, well-provisioned cloud, and code that holds up under load. This role owns that backbone. You will make our systems fast, dependable, and easy for physicists, researchers, and engineers to build on. What You Will Do Your north star will be production and delivering value to our customers. Design, build, and operate the backend services and infrastructure that power Vinci’s simulation and inference platform. Own infrastructure-as-code with Terraform across our cloud environments, provisioning and managing services reliably and repeatably. Build and harden CI/CD pipelines (Jenkins or equivalent) so the team can ship with confidence and strong regression coverage. Maintain and evolve our build systems (CMake, pip/uv) across large Python and C++ codebases. Take early prototypes through iteration and hardening all the way to customer use, in modest iterative steps. “Close the gap” on pre-existing infrastructure where needed, and evolve core platform components as the product grows. Partner closely with Physicists, AI researchers, Software Engineers, and Computational Geometry experts to turn research into dependable systems. What We’re Looking For Qualifications 8+ years of professional software engineering experience, with a strong focus on backend and infrastructure. Infrastructure & cloud: hands-on Terraform experience and production work on at least one major cloud (GCP, AWS, Azure, or similar). CI/CD: built and maintained pipelines with Jenkins or an equivalent CI system. Build systems: comfortable with build tooling such as CMake and Python packaging via pip/uv. Languages: proficient in Python, with working familiarity in C++. Scale: comfortable navigating and contributing to large, multi-language codebases. Have contributed to a production data processing or platform system. We’re very excited to talk with you if you have Experience taking an early-stage prototype to a production environment, at a startup or national lab. Exposure to frontend development. Familiarity with 3D rendering or visualization technologies. Experience supporting ML or scientific-computing workloads (PyTorch, NumPy, CUDA, GPU infrastructure). Experience with containers and orchestration (Docker, Kubernetes) and observability tooling. Engineering Expectations Strong software engineering fundamentals; comfortable meeting software design standards to get code into a production environment. Capable of leveraging pre-existing infrastructure and “closing the gap” on occasion. Strong CI, regression testing, and validation discipline. Comfort evolving core platform and model infrastructure. Why Vinci 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. Our Mission & Impact Vinci is building the operator intelligence infrastructure that modern hardware programs rely on daily. We are scaling our solution to accelerate design validation from hours to seconds. You will build the infrastructure that lets our unified model architecture—currently running billion-voxel inference—scale and expand into the transient domain, a key frontier in modeling interactions, deformation, and dynamics. Growth & Opportunity This is a unique opportunity for technical and professional growth. You will help define a foundational abstraction layer early in the company’s trajectory. The team is small, friendly, and accessible, and you will be empowered to own and architect large pieces of the system alongside Physicists, AI researchers, Software Engineers, and Computational Geometry experts, including greenfield opportunities to expand Vinci’s core capabilities. Leadership You will work with spectacular technical leaders like CTO Sarah Osentoski and CEO Hardik Kabaria, whose vision is to greatly accelerate physics simulations with ML while retaining solver-grade accuracy.