Key skills
PythonAIMLNLPGenerative AILLMRAGLangChainAgenticAutoGenLangGraphLeadership
About this role
Role Overview
- Lead experimentation and model development for AI/ML solutions in legal products
- Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies)
- Define agentic workflows and reasoning strategies for multi-step legal tasks
- Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality)
- Analyze large-scale legal datasets to extract insights and improve model performance
- Establish best practices for model evaluation, validation, and benchmarking
- Translate experimental results into clear product recommendations and business impact
- Collaborate with product, legal experts, and engineers to align solutions with user needs
- Mentor team members and provide technical leadership in data science and AI
Requirements
- Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics)
- Demonstrates strong experience in NLP, and LLM-based modeling
- Strong experience with generative AI techniques (e.g., prompt engineering, RAG)
- Experienced in designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases
- Ability to design workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases
- Proficiency in Python and data analysis tools
- Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality)
- Able to analyze large-scale legal datasets to extract insights and improve model performance
Tech Stack
- Python
Benefits
- country specific benefits
- annual incentive bonus