JOB DESCRIPTION:
As a data scientist on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments. You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets including matter and contract repository, invoice/legal spend data and work management. You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators. You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company.
RESPONSIBILITIES
• Develop and implement LLM-based applications tailored for in-house legal
• Fine-tune and deploy large language models to enhance their performance on legal text processing tasks
• Evaluate and help maintain our data assets and training/evaluation data sets
• Design and build pipelines for preprocessing, annotating, and managing legal document datasets
• Collaborate with legal experts to understand requirements and ensure models meet domain-specific needs
• Conduct experiments and evaluate model performance to drive continuous improvements
• Interface with other technical personnel or team members to finalize requirements.
• Work closely with other development team members to understand moderately complex product requirements and translate them into software designs.
• Successfully implement development processes, coding best practices, and code reviews for production environments.
REQUIREMENTS
• Formal training in machine learning: dimensionality reduction, clustering, embeddings, and sequence classification algorithms
• Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers.
• Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, TensorFlow, Keras, PyTorch, Flair, BERT
• Practical experience with large language models, prompt engineering, fine-tuning and benchmarking, using frameworks such as LangChain and LlamaIndex
• Strong Python background
• Knowledge of AWS, GCP, Azure, or other cloud platform
• Understanding of data modeling principles and complex data models.
• Proficiency with relational and NoSQL databases as well as vector stores (e.g., Postgres, Elasticsearch/OpenSearch, ChromaDB)
• Knowledge of Scala, Spark, Ray, or other distributed computing systems highly preferred
• Knowledge of API development, containerization, and machine learning deployment highly preferred• Experience with ML Ops/AI Ops highly preferred
PREFERRED QUALIFICATIONS
• MS in Data Science, Computer Science, Statistics, Machine Learning, or related field
• 2+ years of relevant work experience
• Or undergraduate degree in relevant field and 4+ years of relevant work experience
****TOP 3 REQUIRED SKILLS:
1. Natural Language Processing
2. LLM/Generative AI/ GenAI Application Development
3. Python
