The Science pillar advances LLM research, fine‑tuning, evaluation frameworks, anomaly detection, and frontier model development—partnering closely with Platform Engineering, SRE, and Pods/Business Engagement to ship production-grade agents and platform features
Job Summary
The Science pillar advances LLM research, fine‑tuning, evaluation frameworks, anomaly detection, and frontier model development—partnering closely with Platform Engineering, SRE, and Pods/Business Engagement to ship production-grade agents and platform features.
This role will focus on applied research and product-oriented data science requirements – designing and validating domain-specific LLM solutions, building evaluation taxonomies and metrics and operationalizing fine-tuning/tooling for business use cases.
State Street is one of the largest custodian banks, asset managers and asset intelligence companies in the world, making our mark on the financial services industry for over two centuries.
Matching Summary
The Science pillar advances LLM research, fine‑tuning, evaluation frameworks, anomaly detection, and frontier model development—partnering closely with Platform Engineering, SRE, and Pods/Business Engagement to ship production-grade agents and platform features.
Skills & Requirements
Must-have
LLM research and fine-tuning
evaluation frameworks and taxonomies
knowledge graphs and embeddings
inference engine development
production-grade AI solutions
Nice-to-have
agentic AI workflows
domain-specific LLM solutions
semantic search and reasoning
cost optimization for inference
Key Requirements
3+ years of experience in applied ML or NLP
Hands-on experience with LLM’s, GenAI or NLP at production scale