About Vinci
We’re building a copilot for hardware. Software engineers have powerful AI tools. Hardware engineers still rely on workflows that take hours or days to simulate and iterate. Vinci is changing that.
Our platform combines AI, geometry processing, and physics simulation to help engineers validate designs dramatically faster than traditional tools. The system integrates foundation models with simulation engines to produce full-fidelity physical predictions in seconds instead of hours.
We’re a small team building infrastructure that connects AI models, large-scale simulation data, and production software used directly by engineers.
The Role
We’re looking for a backend engineer who enjoys building systems that sit between data infrastructure and real product features.
This role spans two major areas:
Data generation systems
Build pipelines that generate and process large datasets used for training and evaluating models
Manage simulation outputs, geometry data, and experiment artifacts
Develop tools for validating, transforming, and curating datasets
Product backend
Build and maintain APIs used by the Vinci product
Develop integrations with models, simulation engines, and external tools
Design services that support the core user workflows of the platform
You’ll work across the stack with ML engineers, physics researchers, and product engineers.
What We’re Looking For
We value engineers who are comfortable moving between infrastructure, data systems, and product code, and who enjoy building pragmatic systems that ship.
Backend Engineering
Experience building and operating production backend services
Strong experience designing APIs and service architectures
Ability to write clean, maintainable, well-tested code
Experience debugging and improving performance, reliability, and observability
Comfortable integrating external services, APIs, and internal models
Ability to work across teams to translate product requirements into system design
Data & Pipeline Systems
Experience building data pipelines or large-scale processing workflows
Familiarity with batch processing, distributed systems, or workflow orchestration
Experience managing large datasets and data transformations
Comfort working with compute-heavy workloads and long-running jobs
Systems & Infrastructure
Experience deploying and operating systems in cloud environments (AWS, GCP, or similar)
Familiarity with containerized services and modern deployment workflows
Ability to design systems that balance throughput, latency, and cost
How We Work
We’re a small team and engineers own large pieces of the system. That means:
Designing systems, not just implementing tickets
Shipping features that go directly into the product
Working closely with researchers and customers