Data Scientist – Graph RAG, LLM Fine-Tuning
State Street
full-time
Posted on:
Location Type: Office
Location: Bangalore • 🇮🇳 India
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudGoogle Cloud PlatformNeo4jPythonPyTorchScikit-LearnTensorflow
About the role
- Design and implement Graph RAG pipelines for enterprise-scale knowledge retrieval and contextual generation.
- Fine-tune LLMs (e.g., GPT, LLaMA, Mistral) using domain-specific datasets to improve performance on targeted tasks.
- Develop and maintain knowledge graphs and embeddings for semantic search and reasoning.
- Collaborate with engineering teams to deploy scalable AI solutions in production environments.
- Conduct experiments and evaluations to benchmark model performance and ensure robustness.
- Stay up-to-date with the latest research in NLP, graph neural networks, and LLM architectures.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
- 3+ years of experience in applied machine learning or NLP.
- Hands-on experience with LLM fine-tuning using frameworks like Hugging Face Transformers, DeepSpeed, or LoRA.
- Strong understanding of graph databases (e.g., Neo4j, RDF, DGL) and knowledge graph construction.
- Proficiency in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn).
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
Benefits
- Generous medical care
- Insurance and savings plans
- Flexible Work Programs
- Development programs and educational support
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Graph RAG pipelinesLLM fine-tuningknowledge graphsembeddingssemantic searchPythonPyTorchTensorFlowScikit-learngraph databases