Machine Learning Engineer II

Build agentic AI systems for financial data at S&P Global in New York, NY (onsite), spanning LLM orchestration, retrieval, evaluation, and the full ML lifecycle.

Responsibilities

• Address distinctive challenges in agentic design and LLM orchestration, including context engineering, data access patterns, memory management, and agent performance evaluation
• Contribute across the ML lifecycle, from problem framing and data exploration to experimentation, deployment, and monitoring in production for continuous improvement of Agentic Systems
• Apply advanced NLP techniques using proprietary unstructured and structured datasets to extract insights and create solutions tied to business value
• Partner with Data, Product, Design, and Engineering teams to design and develop Agents that improve user experience and support business objectives
• Collaborate with ML Operations to automate the full ML systems lifecycle, from initial technical design through implementation

Requirements

• Bachelor’s degree (or higher) in Computer Science, Engineering, or a related field
• 3+ years of significant, hands-on industry experience in machine learning, NLP, and information retrieval systems, focused on practical applications
• Experience covering all phases of the ML life-cycle, including designing, experimenting, deploying, and maintaining production systems
• Strong Python skills and familiarity with software development best practices
• Experience using machine learning libraries and frameworks for agent orchestration, including LangGraph and pydanticAI (and similar tools)
• Knowledge of agentic design, including user interaction understanding and agent performance evaluation to enhance user experiences
• Strong habits in coding, documentation, collaboration, and communication
• Proven problem-solving ability and a proactive approach to tackling challenges
• Ability to adapt in a fast-paced and dynamic work environment

Technologies

• Agentic Orchestration
• Deep Research
• Information Retrieval
• Semantic Search
• LLM code generation
• LLM tool utilization
• Textual RAG systems
• LangGraph
• Transformers
• HuggingFace
• LightGBM
• PyTorch
• SKLearn
• XGBoost
• Jupyter
• Matplotlib
• Pandas
• Weights & Biases
• Langfuse
• Apache Spark
• AWS Athena
• DVC
• LabelBox
• OpenSearch
• Postgres/Pgvector
• S3
• SQLite
• Arize
• Airflow
• AWS
• DeepSpeed
• Docker
• Grafana
• Jenkins
• LangFuse
• LiteLLM
• Ray
• vLLM
• Claude Code
• FastAPI
• Streamlit
• Gradio
• Python
• pydanticAI

Benefits

• 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, plus 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

Recruitment Fraud Alert

• If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to [email protected]
• S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment