Machine Learning Engineer II

S&P Global

Machine Learning Engineer building production RAG systems for Kensho, S&P Global’s AI innovation hub. Developing retrieval pipelines, LLM orchestration, embeddings, vector search, and GraphRAG.

Posted 8/11/2026full-timeNew York City • Massachusetts, New York • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing end-to-end RAG pipelines, leveraging advanced machine learning techniques and frameworks to optimize retrieval systems and enhance user experiences. Proficient in Python programming and familiar with vector databases and LLM orchestration libraries.

Highest-signal resume keywords

Machine LearningNatural Language ProcessingPython ProgrammingLLM OrchestrationVector Databases

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningNatural Language ProcessingInformation Retrieval SystemsLarge-Scale Text ProcessingPython ProgrammingData ProcessingML PipelinesVector Indexing AlgorithmsChunking AlgorithmsEmbedding Models

Soft Skills

Problem-SolvingCollaborationCommunicationAdaptabilityProactive Approach

Tools & Technologies

PyTorchTransformersHuggingFaceLangChainLlamaIndexPostgreSQL/PGVectorOpenSearchPinecone

Industry Keywords

RAG PipelinesData RetrievalSimilarity SearchUnstructured Data RetrievalML Systems Lifecycle

Tech Stack

Tools & technologies

PostgresPythonPyTorch

About the role

Key responsibilities & impact

Design and implement end-to-end RAG pipelines integrating proprietary chunking algorithms, embedding models, vector databases, and data retrieval agents
Build and optimize retrieval systems over large-scale proprietary datasets using advanced embedding techniques
Develop LLM-based solutions orchestrating retrieval, generation, and ranking for high-quality, context-aware responses
Investigate and solve challenges in vector search, chunking and indexing strategies, unstructured data retrieval evaluation, and GraphRAG
Work with Product and Design teams to build ML-based solutions that enhance user experiences and meet business objectives
Collaborate with ML Operations to automate management of the full ML systems lifecycle from technical design through implementation

Requirements

What you’ll need

Bachelor's degree or higher in Computer Science, Engineering, or a related field
3+ years of hands-on industry experience with machine learning, NLP, information retrieval systems, and large-scale text processing
Experience designing, shipping, and maintaining production systems
Strong Python programming skills
Working knowledge of data processing tools and ML frameworks such as PyTorch, Transformers, and HuggingFace
Experience with LLM orchestration libraries/frameworks such as LangChain and LlamaIndex
Experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation
Experience with vector databases such as PostgreSQL/PGVector, OpenSearch, and Pinecone
Understanding of similarity search techniques and vector indexing algorithms
Effective coding, documentation, collaboration, and communication habits
Strong problem-solving skills and a proactive approach
Ability to adapt to a fast-paced and dynamic work environment

Benefits

Comp & perks

Annual incentive bonus
Equity plans
Medical, Dental, and Vision insurance
100% company paid premiums
Unlimited Paid Time Off
26 weeks of 100% paid Parental Leave (paternity and maternity)
401(k) plan with 6% employer matching
Generous company matching on donations to non-profit charities
Up to $20,000 tuition assistance toward degree programs
Up to $4,000/year for ongoing professional education such as industry conferences
Plentiful snacks, drinks, and regularly catered lunches
Dog-friendly office (CAM office)
Bike sharing program memberships
Compassion leave and elder care leave
Mentoring and additional learning opportunities
Opportunity to expand professional network and participate in conferences and events