Lead ML/NLP Engineer (Architect)

We’re looking for a Lead NLP/ML Engineer (Document Intelligence Architect) to join a cutting-edge team building an AI-powered platform for legal intelligence. You’ll take the lead on developing advanced NLP and reasoning pipelines that transform vast collections of legal documents into actionable insights.

In this role, you’ll design systems that do more than extract data — they understand legal context, identify patterns across cases, and assist in drafting tailored legal documents. Think of it as building the brain of an AI paralegal.

What You’ll Do

• Build robust NLP pipelines to:
  • Extract structured data from legal documents (e.g., PTAB, CAFC)
  • Summarize and analyze documents to answer user questions
  • Identify trends and legal arguments across multiple cases
• Design Retrieval-Augmented Generation (RAG) systems for multi-document reasoning using LLMs (e.g., GPT-4, Claude, Gemini)
• Develop legal content generation tools using templates and prompts (e.g., draft petitions, responses)
• Incorporate analytics on judges, parties, and case metadata into intelligent workflows
• Collaborate closely with engineering and product to shape infrastructure, model deployment, and content generation pipelines

What We’re Looking For

• 7+ years of experience in Machine Learning/NLP, with production-grade systems
• Expertise in building complex NLP workflows using LLMs (RAG, summarization, prompt engineering)
• Solid understanding of domain-specific NLP — ideally in legal or technical contexts
• Hands-on experience with HuggingFace, LangChain, OpenAI API, or similar tools
• Strong Python skills and experience with pipeline orchestration tools (Airflow, Ray, etc.)
• Familiarity with GCP services like BigQuery, GCS, and Cloud Functions
• Ability to lead architecture decisions and mentor other engineers

Nice to Have

• Background in legal tech, IP litigation, or experience working with government/legal datasets
• Familiarity with IPRs, PTAB, or USPTO databases
• Experience designing annotation or labeling tools
• Comfortable working in agile, product-driven remote teams