Applied Machine Learning Engineer

PermitFlow

. Design, implement, and optimize LLM-powered models for document processing, data extraction, and permit workflow automation .

Posted 10/9/2026full-timeNew York City • New York • United StatesMid-LevelSenior💰 $175,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing LLM-powered models for document processing and data extraction, with a strong focus on NLP tasks and scalable ML infrastructure. Proven ability to deploy and iterate on ML systems that deliver measurable business impact in fast-paced environments.

Highest-signal resume keywords

Machine Learning EngineeringNatural Language Processing (NLP)LLM Expertise (OpenAI GPT, Claude, Hugging Face)Python ProficiencyCloud ML Infrastructure (AWS, GCP, Azure)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EngineeringNatural Language Processing (NLP)LLM ExpertiseRetrieval-Augmented Generation (RAG)PythonML Frameworks (PyTorch, TensorFlow)System DesignDeployment and Scaling of ML SystemsData ExtractionDocument Processing

Soft Skills

CollaborationAutonomyArchitectural Thinking

Tools & Technologies

FAISSElasticsearchPineconeWeaviateML Infrastructure

Industry Keywords

Document ProcessingData ExtractionPermit Workflow AutomationJurisdictional DataRegulatory Data

Tech Stack

Tools & technologies

AWSAzureCloudElasticSearchGoogle Cloud PlatformPythonPyTorchTensorflow

About the role

Key responsibilities & impact

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 NLP tasks including 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, high-impact AI features
Collaborate with engineering, product, and domain experts on ML-powered solutions for pre-construction challenges

Requirements

What you’ll need

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
Ability to work 3 days per week (M/W/F) in the NYC office
Legally authorized to work in the United States

Benefits

Comp & perks

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
Paid family leave
Home office & equipment stipend
Daily in-office lunch and dinner provided
Commuter benefits (pre-tax transit and parking)