Posted by employer 1 day ago
First seen on Joblaze 5 months ago
Last verified on the company career page 13 hours ago
Skills & Technologies
Requirements
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
In the role of Applied Machine Learning Engineer at PermitFlow, the individual will focus on developing and optimizing machine learning models that enhance document processing and automate permitting workflows. Key skills include expertise in natural language processing, large language models, and experience with retrieval systems, alongside proficiency in Python and cloud ML infrastructure. This position is ideal for seasoned professionals with a strong background in machine learning engineering who thrive in dynamic startup environments. PermitFlow's mission to transform the construction industry through AI offers a unique opportunity to impact a $1.6 trillion sector.
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Quick facts
From the original posting
Our HQ is in New York City with a hybrid schedule (3 in-office days per week). Preference for NYC-based candidates or those open to relocation.
As an Applied Machine Learning Engineer, you will develop the ML foundation for PermitFlow’s AI agents. You’ll 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.
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 in a high-growth company
401(k) savings plan
Unlimited PTO and paid family leave
Home office & equipment stipend
Daily in-office lunch and dinner provided
Commuter benefits (pre-tax transit and parking)
Standard company text repeated across PermitFlow's postings is omitted here.