HighArc
Prototype Engineer
About this role
Higharc seeks a Prototype Engineer to bridge AI/ML research and production capabilities on their homebuilding platform. You'll integrate experimental models and research outputs into the product, work across Python and TypeScript stacks, and collaborate with customers to validate and refine new features.
What you'll do
- Design tools exposing AI/ML capabilities to autonomous agents for production homebuilding use-cases
- Integrate research outputs into the Higharc product as packages and components
- Wire new capabilities end-to-end across Python ML services and TypeScript/React frontend via API
- Build frameworks for rapid prototype evaluation, iteration, and promotion
- Translate between research and product engineering teams, converting notebooks and models into maintainable code
- Participate in customer-facing labs to validate prototypes and inform priorities
What they're looking for
- Python and TypeScript/React
- AI/ML integration into production systems
- LLM APIs (OpenAI, Anthropic, open-source)
- Vector databases and RAG architectures
- API design and evaluation design
- PyTorch, HuggingFace, and ML ecosystem tools
- CI/CD and testing frameworks
- Agentic frameworks (LangChain, CrewAI)
Benefits
- Competitive salary with significant equity
- Comprehensive medical, dental, and vision coverage
- Flexible PTO and remote-first work environment
- Meaningful maternity/paternity leave
- Short and long-term disability plans and 401K
- Home office stipend for remote setup
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HighArc
HighArc is a VC-backed startup building AI-powered software to transform home design and construction workflows for homebuilders. The company is hiring full-stack engineers, solutions engineers, research engineers, and prototype engineers to develop core platform features including showroom experiences, pricing and configuration rule engines, spatial AI capabilities, and research-to-production integrations.
View all jobs at HighArcLikely interview questions
- Walk us through a time you shipped an AI/ML feature to production users. What were the biggest challenges in moving from research/prototype to actual product?
- Describe your experience bridging research and product engineering teams. How do you handle disagreements about what's technically feasible vs. what's needed for production?