Sr Data Scientist

RELX

Python (advanced proficiency)
Machine learning (supervised/unsupervised learning, nlp)
Generative ai (llms, prompt engineering, embeddings)
Design, develop, and deploy machine learning and GenAI solutions in production environments

Job Summary

  • Design, develop, and deploy machine learning and GenAI solutions in production environments.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines and fine-tune Large Language Models (LLMs).
  • Collaborate with Engineering, Product, and SMEs to deliver AI-driven features and contribute to architecture design for AI-powered systems.

Matching Summary

Design, develop, and deploy machine learning and GenAI solutions in production environments.

Skills & Requirements

Must-have

  • 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
  • LangChain / LlamaIndex
  • Scikit-learn / XGBoost / LightGBM
  • PyTorch / TensorFlow
  • HuggingFace / OpenAI / LLM APIs
  • Vector databases (Pinecone, FAISS, Weaviate, OpenSearch, etc.)
  • SQL and data querying
  • AWS / Azure / GCP experience
  • CI/CD for ML deployments
  • Model tracking tools (MLflow preferred)

Nice-to-have

  • Experience in legal, regulatory, or publishing domains
  • Model monitoring and MLOps
  • Fine-tuning techniques (LoRA, PEFT, QLoRA)
  • Multi-agent frameworks (AutoGen, LangGraph, etc.)

Key Requirements

  • 6–8 Years Experience

Work Rights

Not specified

Tailored Resume

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