Machine Learning Engineer - Summer Intern 2027
S&P Global3 days ago
Responsibilities
- Solve challenges in agentic design and LLM orchestration, including context engineering, data access patterns, memory management, and agent-performance evaluation.
- Lead a project to prototype, build, and test machine learning models and pipeline components under the guidance of senior engineers.
- Gain hands-on experience across the ML model lifecycle, including problem framing, model selection, pipeline development, evaluation, and deployment support.
- Collaborate with ML Engineers, Product Managers, Designers, and Full-Stack Engineers while receiving mentorship and feedback.
Requirements
- No particular credential or amount of experience is required.
- Most successful candidates will be pursuing a bachelor’s degree or higher with relevant machine learning coursework or internship experience.
- Experience designing and iterating on agentic systems, understanding user interactions, and evaluating agent performance is preferred.
- Experience with advanced machine learning methods and modeling real data, along with statistical knowledge and intuition, is preferred.
- Proficiency in Python and Python-based machine learning frameworks such as LangGraph, Pydantic AI, and PyTorch is preferred.
- Effective coding, documentation, communication, and ability to explain complex methods and results to broad audiences are preferred.
Benefits
- Interns receive active mentorship, continuous feedback, and opportunities to attend technical and non-technical discussions and company-wide social events.
- The role offers a collaborative, communicative, team-based environment with experienced engineers.
- Interns are required to work in person from the Cambridge headquarters or New York City office.
Tech Stack
Apache AirflowApache SparkAWSDockerDVCFastAPIGrafanaJenkinsLightGBMMatplotlibPandasPostgreSQLPythonPyTorchscikit-learnSQLiteXGBoost