Job description

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, permitflow.com from top-tier investors including Accel, Kleiner Perkins linkedin.com, 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 OVERVIEW 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. 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 WHAT WE OFFER - Competitive salary and meaningful equity in a high-growth company - 100% company-paid base medical, dental, and vision coverage for employees + healthcare FSA - 401(k) savings plan - Unlimited PTO and paid family leave - Home office & equipment stipend - Daily in-office lunch and dinner provided - Commuter benefits (pre-tax transit and parking) PermitFlow 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 identity, gender expression, or family status, as protected by applicable law. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities. All employment decisions are based on merit, qualifications, and business needs.

Requirements

Must-haves

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.
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
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

Nice-to-haves

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Application prep

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Keywords to mirror

aimachine learningmlllmpythonawsgcpazure

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto