Description

You will develop and implement LLM-based applications for legal text processing and drive new product development within a small team.

Responsibilities

• Develop, fine-tune, and deploy large language models to enhance performance on legal text tasks.
• Design and build pipelines for preprocessing, annotating, and managing large-scale natural language datasets.
• Prototype new ideas and conduct experiments to evaluate model performance and drive continuous improvements.
• Implement development processes, coding best practices, and code reviews for production run-time and build-time environments.
• Collaborate with product designers, data engineers, and legal experts to translate complex requirements into software designs.

Required Skills

• Strong Python background with experience writing production code.
• Practical experience with NLP libraries including spaCy, word2vec, Flair, and BERT.
• Deep learning expertise using PyTorch, TensorFlow, and Keras.
• Experience with LLMs, prompt engineering, fine-tuning, and benchmarking using LangChain or LlamaIndex.
• Formal training in machine learning, including dimensionality reduction, clustering, embeddings, and sequence classification.
• Proficiency with relational/NoSQL databases and vector stores such as Postgres, Elasticsearch/OpenSearch, or ChromaDB.
• Knowledge of cloud platforms including AWS, GCP, or Azure.
• Understanding of data modeling principles and complex data models.

Preferred Skills

• Knowledge of Scala, Spark, Ray, or other distributed computing systems.
• Experience with API development, containerization, and machine learning deployment.

Key Skills

Education

Bachelor's degree