PermitFlow
About PermitFlow
PermitFlow is building AI agents for the $1.6T construction industry. We're creating the leading pre-construction platform, starting with the $12B permitting market.
Our platform automates the slow, manual permitting process for builders, covering everything from jurisdiction research to application preparation, submission, and real-time tracking. By transforming fragmented regulations and manual workflows into structured, intelligent systems, we help contractors move faster, reduce risk, and scale with confidence.
We've raised $36.5M+ with Kleiner Perkins leading our Series A, joined by Initialized Capital, Y Combinator, Felicis Ventures, and Altos Ventures. Our backers include founders and executives from OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber.
We are a team of architects, engineers, permitting experts, and product builders who have felt the pain of pre-construction firsthand and are committed to fixing it. Demand is growing faster than we can meet, and we're hiring top talent to help us scale.
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
PermitFlow is building AI agents for the $1.6T construction industry. We're creating the leading pre-construction platform, starting with the $12B permitting market.
Our platform automates the slow, manual permitting process for builders, covering everything from jurisdiction research to application preparation, submission, and real-time tracking. By transforming fragmented regulations and manual workflows into structured, intelligent systems, we help contractors move faster, reduce risk, and scale with confidence.
We've raised $36.5M+ with Kleiner Perkins leading our Series A, joined by Initialized Capital, Y Combinator, Felicis Ventures, and Altos Ventures. Our backers include founders and executives from OpenAI, Google, Procore, ServiceTitan, Zillow, PlanGrid, and Uber.
We are a team of architects, engineers, permitting experts, and product builders who have felt the pain of pre-construction firsthand and are committed to fixing it. Demand is growing faster than we can meet, and we're hiring top talent to help us scale.
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