Applied Machine Learning Engineer
New York City, NY · New York City, New York, USA
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- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
If hired by PermitFlow, will you now or in the future require sponsorship for employment visa status (e.g. H-1B, TN, OPT, etc.)?
From the employer’s application form
What you’ll work on
Full postingAs an Applied Machine Learning Engineer, you will develop the ML foundation for PermitFlow’s AI agents.
Design and deploy LLM-powered models for document processing and permit workflow automation
Build retrieval-augmented generation pipelines for jurisdictional and regulatory data
Fine-tune and evaluate pre-trained models for classification, entity recognition, and summarization
Build scalable ML infrastructure and backend services that run in production
Own the full ML lifecycle: experimentation, deployment, monitoring, and iteration
From the employer’s posting
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.
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
Own the full ML lifecycle: experimentation, deployment, monitoring, evaluation, and iteration
Tools in this posting
- Python
- AWS
- Azure
- Elasticsearch
- GCP
- Hugging Face
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 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
- 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
- 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
- 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)
Benefits in the posting
Full benefits wording- 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)
- 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.
From the employer’s posting.
Posting record
Report an errorMay be filledThe employer has taken this posting down, so the role may be filled. Check their website before applying.
- Status in our records
- No longer listed
- First seen by us
- Jun 2, 2026 · 150 days ago
- Recorded sightings
- 25
- Last seen by us
- Oct 29, 2026
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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, 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 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
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.
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- Pay
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- Location & working pattern
New York City, New York, USA
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 Overview
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