Machine Learning Engineer II

Join S&P Global as a mid-level Machine Learning Engineer II focused on building agentic AI systems for financial data. The role emphasizes LLM orchestration, retrieval and evaluation, and end-to-end delivery from experimentation through productionization, with a strong focus on connecting data to actionable insights.

Key Responsibilities

• Solve distinct challenges in agentic design and LLM orchestration, including context engineering, data access patterns, memory management, and evaluating agent performance against user needs.
• Contribute across the machine learning lifecycle, including problem framing, data exploration, model experimentation, deployment, and monitoring in production to continuously improve Agentic Systems.
• Apply advanced NLP methods to leverage proprietary unstructured and structured datasets, extracting insights and building solutions that support business value.
• Partner with Data, Product, Design, and Engineering teams to design and build Agents that enhance user experiences and align to business objectives.
• Work closely with the ML Operations team to develop automated capabilities for managing the ML systems lifecycle, from technical design to implementation.

Required Qualifications

• 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, with emphasis on practical application.
• Experience spanning the full ML lifecycle, including designing, experimenting, deploying, and maintaining production systems.
• Strong proficiency in Python with an understanding of software development best practices.
• Experience using machine learning libraries and frameworks for agent orchestration, such as LangGraph and pydanticAI.
• Experience with agentic design, including an understanding of user interactions and agent evaluation to improve user experiences.
• Demonstrated habits related to effective coding, documentation, collaboration, and communication.
• Strong problem-solving skills and a proactive approach to addressing challenges.
• Ability to adapt in a fast-paced and dynamic work environment.

Tools & Technologies

• Agentic Orchestration, Deep Research, Information Retrieval, Semantic Search
• LLM code generation and 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

Compensation

USD 140,000 - 180,000 per year.

Location & Work Mode

New York, NY (onsite).

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.