Applied Machine Learning Engineer

• 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

• 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
• 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

Compensation Range: $175K - $245K