Chief Data Science Engineer

hace 3 semanas


Xico, México Lexisnexis Risk Solutions A tiempo completo
About LexisNexis Legal & Professional

We are a global leader in providing information-based analytics and decision tools for professional and business customers.

Leveraging our expertise in AI and advanced technologies, we improve productivity and transform the business and practice of law.

Role Summary

This role is part of a small team environment where you will work on new product development 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.

Responsibilities
  • Develop and implement LLM-based applications tailored for legal use-cases
  • 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 ML-applications meet domain-specific needs
  • Conduct experiments and evaluate model performance to drive continuous improvements
  • Fine-tune and deploy large language models to enhance their performance on legal text processing tasks
  • Interface with other technical personnel or team members to finalize requirements
  • Work closely with other development team members to understand complex product requirements and translate them into software designs
Requirements
  • Practical experience with large language models, prompt engineering, fine-tuning RAG-based applications and benchmarking, using frameworks such as LangChain
  • 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., MySQL, Postgres, Solr, Elasticsearch/OpenSearch)
  • Knowledge of Spark-Scala, Ray or other distributed computing systems highly preferred
  • Knowledge of API development, containerization, and machine learning deployment highly preferred
Estimated Salary: $85,000 - $120,000 per year

The salary range is based on national averages and may vary depending on location and qualifications.



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