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PermitFlow · Posted 2w ago

Applied Machine Learning Engineer

$175–250K/yrHybrid

Job relayed by Stapply Data, its source: you apply there.

Location
🇺🇸 United States
Contract
Full-time
Role
ML engineering
Source
Stapply Data

Stack

  • PyTorch
  • TensorFlow
  • Hugging Face
  • LLM
  • Vector DB
  • Elasticsearch
  • Python
  • AWS
  • GCP
  • Azure

The posting

Join PermitFlow as an Applied Machine Learning Engineer, where you will develop the ML foundation for our AI agents. You will 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. This role offers equity packages, 100% paid health, dental & vision coverage, a company-issued laptop, home office & equipment stipend, lunch & dinner via UberEats, commuter benefits, team building events, and unlimited PTO.

- Développer la fondation ML pour les agents d'IA de PermitFlow, concevoir, prototyper et déployer des systèmes intelligents. - Posséder le cycle de vie complet de l'IA, de la recherche sur les modèles et l'ingénierie des données au déploiement en production. - Collaborer avec les équipes d'ingénierie, de produit et d'experts en la matière pour façonner des solutions alimentées par l'IA.

- Comfort operating in fast-moving startup environments with high ownership and autonomy - Strong system design and architectural thinking, with a bias toward shipping and iterating quickly - Experience building retrieval and vector search systems (e.g., FAISS, Elasticsearch, Pinecone, Weaviate) - Strong track record of deploying and scaling ML systems with measurable business impact - 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 with cloud ML infrastructure (AWS, GCP, or Azure) - Proficiency in Python and ML frameworks like PyTorch or TensorFlow