About our Team:

LexisNexis Legal Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today s top model creators for each individual legal use case.

About The Role:

The Sr. Data Scientist to work on complex project involving AI, GenAI, RAG and Agentic Solution for the business delivery projects

Responsibilities

Design, develop, and deploy machine learning and GenAI solutions in production environments
Build and optimize Retrieval-Augmented Generation (RAG) pipelines
Fine-tune and evaluate Large Language Models (LLMs)
Develop prompt engineering strategies and evaluation frameworks
Implement scalable ML pipelines using Python
Work with structured and unstructured data sources
Collaborate with Engineering, Product, and SMEs to deliver AI-driven features
Monitor model performance, drift, and reliability in production
Conduct experimentation, A/B testing, and performance benchmarking
Contribute to architecture design for AI-powered systems

Requirements

Experience: 6 8 Years

Core Stack

Python (advanced proficiency)
Machine Learning (supervised/unsupervised learning, NLP)
Generative AI (LLMs, prompt engineering, embeddings)
RAG architecture and vector search
Model evaluation and validation frameworks

ML AI Tools

LangChain / LlamaIndex (or similar frameworks)
Scikit-learn / XGBoost / LightGBM
PyTorch / TensorFlow
HuggingFace / OpenAI / LLM APIs
Vector databases (Pinecone, FAISS, Weaviate, OpenSearch, etc.)

Data Infrastructure

SQL and data querying
Experience with AWS / Azure / GCP
CI/CD for ML deployments
Model tracking tools (MLflow preferred)

Good to Have

Experience in legal, regulatory, or publishing domains
Experience with model monitoring and MLOps
Knowledge of fine-tuning techniques (LoRA, PEFT, QLoRA)
Experience with multi-agent frameworks (AutoGen, LangGraph)

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Senior Data Scientist I

Job Description

No Referrers Available