Applied Machine Learning Engineer
$175k - $250k • New York City, NY • FullTime
Posted 8d ago
About the job
PermitFlow is seeking an Applied Machine Learning Engineer to develop the ML foundation for their AI agents, which are redefining how America builds by tackling complex information challenges in the construction industry. This role involves designing, prototyping, and deploying intelligent systems for document processing, insight extraction, and autonomous permitting workflows. You will own the end-to-end ML lifecycle, from research and data engineering to production deployment and continuous evaluation, contributing to the AI infrastructure that accelerates housing, clean-energy, and infrastructure development.
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 NLP tasks like classification, entity recognition, and summarization.
- Build scalable ML infrastructure and backend services, integrating models into production systems.
- 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.
Requirements
- 5+ years of experience in machine learning engineering, with production ML experience.
- Deep expertise in NLP and LLMs (e.g., 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% 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)