🚀 About PermitFlow

PermitFlow is redefining how America builds. Pre-construction remains one of the most broken and manual parts of the $1.6T construction industry, causing massive delays, wasted capital, and lost opportunity across the built world. Our AI workforce delivers unprecedented speed, accuracy, and visibility to pre-construction — accelerating housing development, enabling clean-energy projects, and driving economic growth in communities nationwide. To date, we’ve powered over $20B in real estate development, helping builders and contractors move faster, reduce risk, and scale with confidence.

We’re entering hypergrowth with clear product-market fit and a world-class team from top AI and construction companies. We’ve raised over $36.5M from Kleiner Perkins, Initialized Capital, Y Combinator, Felicis Ventures, and Altos Ventures, alongside backers from OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber. We are on a mission is to modernize how the built world operates.

Our HQ is in New York City with a hybrid schedule (3 in-office days per week). Preference for NYC-based candidates or those open to relocation.

✅ What You’ll Do

As an Applied Machine Learning Engineer , you will develop the ML foundation for PermitFlow’s AI agents. You’ll design, prototype, and deploy intelligent systems that process documents, extract insights, and power autonomous permitting workflows. You will own the end-to-end ML lifecycle, from model research and data engineering to production deployment and continuous evaluation.

You will:

• Design, implement, and optimize LLM-powered models for document processing, data extraction, and permit workflow automation

• Develop retrieval-augmented generation (RAG) pipelines and search/retrieval systems for jurisdictional and regulatory data

• Rapidly prototype, fine-tune, and evaluate pre-trained models for real-world NLP tasks like classification, entity recognition, and summarization

• Build scalable ML infrastructure and backend services , integrating models into production systems that power AI agents

• Work with large structured and unstructured datasets to improve indexing, retrieval, and contextual accuracy

• Own the full ML lifecycle : experimentation, deployment, monitoring, evaluation, and iteration

• Balance ML, retrieval, and rule-based approaches to ship reliable, maintainable, and high-impact AI features

• Collaborate with engineering, product, and domain experts to shape ML-powered solutions for complex pre-construction challenges

🙌 What We’re Looking For

• 5+ years of experience in machine learning engineering , with production ML experience

• Deep expertise in NLP and LLMs (OpenAI GPT, Claude, Hugging Face models)

• Experience building retrieval and vector search systems (e.g., FAISS, Elasticsearch, Pinecone, Weaviate)

• Proficiency in Python and ML frameworks like PyTorch or TensorFlow

• Strong track record of deploying and scaling ML systems with measurable business impact

• Experience with cloud ML infrastructure (AWS, GCP, or Azure)

• Strong system design and architectural thinking , with a bias toward shipping and iterating quickly

• Comfort operating in fast-moving startup environments with high ownership and autonomy

💙 Benefits

• 📈 Competitive salary and meaningful equity

• 🩺 100% paid health, dental, and vision coverage

• 💻 Company laptop and equipment stipend

• 🍽️ Daily meals via UberEats and a fully stocked kitchen

• 🚍 Commuter benefits

• 🎤 Team building events and offsites

• 🌴 Unlimited PTO