Senior Machine Learning Engineer
Core
Building retrieval-driven AI agents and production-grade ML systems that ground LLM outputs in trusted S&P data for financial intelligence products.
Role type
Senior IC machine learning engineer (GenAI/LLM)
Builds
Retrieval-driven AI agents, LLM-powered applications, and fundamental AI toolkits (e.g., Kensho Link, NERD)
Domain
Financial services, Generative AI, Large Language Models (LLM), Information Retrieval
Deliverable
production ML models
Required skills
Machine Learning fundamentals, Natural Language Processing (NLP), Information Retrieval systems, Python, SQL, ML pipeline design (data processing, training, inference, maintenance, evaluation, versioning), LLM orchestration (LangChain), RAG-based systems
Preferred skills
RAG-based system experience
Technologies
PyTorch, Transformers, HuggingFace, LangChain, Scikit-learn, XGBoost, LightGBM, Docker, Amazon EKS, Jenkins, AWS, Pandas, Matplotlib, Jupyter, Weights & Biases, DVC, MosaicML, NVIDIA NeMo, LabelBox, Postgres, OpenSearch, SQLite, S3
Responsibilities
Create, refine, and deploy machine learning systems to solve complex business problems; Design AI agents that fetch, validate, and structure data from S&P datasets; Identify and resolve performance gaps in LLM-based agents regarding latency, memory, and efficiency; Leverage proprietary structured and unstructured datasets with domain understanding; Optimize and scale ML systems for high demand and reliable production behavior; Propose solutions to reduce technical debt and improve stack reliability; Scope, plan, and execute ML initiatives to develop core capabilities; Collaborate with Data, Product, Design, and Engineering teams; Drive the full ML lifecycle from problem framing to production monitoring.