Applied Machine Learning Engineer

PermitFlow is redefining how America builds. We’re an applied AI company serving the nation’s builders, tackling one of the largest information challenges in the economy: understanding what can be built, where, and how. Our AI agent workforce helps the fastest-growing construction companies navigate everything from permitting and licensing to inspections and project closeouts – accelerating housing, clean-energy, and infrastructure development across the country.Despite being a $1.6T industry, construction still suffers from massive delays, wasted capital, and lost opportunity. PermitFlow has already delivered unprecedented speed, accuracy, and visibility to over $20B in development, helping contractors reduce compliance time, de-risk projects, and scale with confidence.As the U.S. enters a new capex supercycle across data centers, factories, housing, and renewables, joining PermitFlow means building the AI infrastructure at the core of every construction project driving the next wave of reindustrialization.We’ve raised over $90M, most recently completing our Series B, from top-tier investors including Accel, Kleiner Perkins, Initialized, Y Combinator, Felicis, and Altos Ventures, with backing from leaders at 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.Role OverviewAs 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.What You'll DoDesign, implement, and optimize LLM-powered models for document processing, data extraction, and permit workflow automationDevelop retrieval-augmented generation (RAG) pipelines and search/retrieval systems for jurisdictional and regulatory dataRapidly prototype, fine-tune, and evaluate pre-trained models for real-world NLP tasks like classification, entity recognition, and summarizationBuild scalable ML infrastructure and backend services, integrating models into production systems that power AI agentsWork with large structured and unstructured datasets to improve indexing, retrieval, and contextual accuracyOwn the full ML lifecycle: experimentation, deployment, monitoring, evaluation, and iterationBalance ML, retrieval, and rule-based approaches to ship reliable, maintainable, and high-impact AI featuresCollaborate with engineering, product, and domain experts to shape ML-powered solutions for complex pre-construction challengesWhat We’re Looking For5+ years of experience in machine learning engineering, with production ML experienceDeep 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 TensorFlowStrong track record of deploying and scaling ML systems with measurable business impactExperience with cloud ML infrastructure (AWS, GCP, or Azure)Strong system design and architectural thinking, with a bias toward shipping and iterating quicklyComfort operating in fast-moving startup environments with high ownership and autonomyWhat We OfferCompetitive salary and meaningful equity in a high-growth companyComprehensive medical, dental, and vision coverageFlexible PTO and paid family leaveHome office & equipment stipendHybrid NYC office culture (3 days in-office/week) with direct access to leadershipIn-Office Lunch & Dinner ProvidedPermitFlow provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender id ... (truncated, view full listing at source)