Applied Machine Learning Engineer
New York City, NY · 5+ years experience · Full-time · Hybrid · Posted Oct 9, 2026
At a glance
- Experience
- 5+ years experience
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- New York City, NY
About the role
- The Applied Machine Learning Engineer will develop the ML foundation for PermitFlow’s AI agents, designing and deploying intelligent systems for document processing and permit workflow automation.
- This role involves owning the end-to-end ML lifecycle, from research and data engineering to production deployment and continuous evaluation.
Responsibilities
- 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
Requirements
- 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
- Meaningful equity
- 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)
Workplace
- Hybrid schedule with 3 in-office days per week
Skills
- Python
- PyTorch
- TensorFlow
- LLMs
- NLP
- OpenAI GPT
- Claude
- Hugging Face
- FAISS
- Elasticsearch
- Pinecone
- Weaviate
Show all 15 skills
- AWS
- GCP
- Azure
