Machine Learning Engineer II
Job Description
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
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