Overview
Applied Machine Learning Engineer role at PermitFlow. This position focuses on developing ML foundations for PermitFlow’s AI agents and driving end-to-end ML lifecycle from research to production deployment.
Base pay range
$175,000.00/yr - $245,000.00/yr
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 delays, wasted capital, and lost opportunity across the built world. Our AI workforce delivers speed, accuracy, and visibility to pre-construction — accelerating housing development, enabling clean-energy projects, and driving economic growth in communities nationwide. We’ve powered over $20B in real estate development, helping builders and contractors move faster, reduce risk, and scale with confidence. We are 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 investors including Kleiner Perkins, Initialized Capital, Y Combinator, Felicis Ventures, and Altos Ventures, alongside backers from OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber. 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
- 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