AI/ML Engineer Intern

Intuitive•Sunnyvale, CA

About The Position

Intuitive’s Global Access, Value and Economics (GAVE) organization is seeking an AI/ML Engineer Intern for Summer 2027. The intern will support the organization’s mission to generate clinical evidence that drives adoption of robotic-assisted surgery. Within the Global Access and Evidence Management Center of Excellence, the intern will develop a system to optimize evidence management and synthesis, including a tool to identify, deduplicate, validate, and ingest publications related to Intuitive products. The role also involves integrating existing large language model (LLM) pipelines into the solution. The internship provides hands-on experience in software development, data management, machine learning, and systems design, along with opportunities to communicate with cross-functional stakeholders. The internship is expected to last 10–12 weeks, beginning in May or June 2027, and requires approximately 40 hours per week. The work arrangement is remote or hybrid, with at least three opportunities for on-site meetings during the internship. Interns must be enrolled in and returning to an accredited degree-seeking academic program after the internship. Compensation is hourly and prorated based on internship duration; the company also describes benefits and a housing allowance. Actual compensation depends on factors including skills and experience, academic program, year in school, and location.

Requirements

Be currently enrolled in and returning to an accredited degree-seeking academic program after the internship.
Be available to work full-time, approximately 40 hours per week, for a 10–12 week period starting in May or June.
Be enrolled in a Bachelor’s- or Master’s-level degree-seeking program in Computer Science, Data Science, Computer Engineering, or a related field.
Have a strong interest in data science and machine learning.
Be able to collaborate effectively with cross-functional teams and address the needs of multiple stakeholders.
Have strong communication and technical skills to engage effectively with different audiences.
Be a self-driven problem solver able to work with minimal supervision.
Have a strong desire to learn and grow in data science and machine learning.
Have proficiency in Python.
Have a strong understanding of relational databases and SQL.
Have a solid grasp of machine learning concepts and algorithms.
Understand systems thinking and system design principles.

Nice To Haves

Experience with LLM APIs such as OpenAI, Anthropic, or Azure OpenAI, including prompt engineering and structured outputs.
Experience with Agentic AI workflows.
Experience building ETL or data ingestion pipelines for Snowflake.
Experience with NLP techniques such as vector embeddings and semantic similarity.
Familiarity with R.
Experience with scikit-learn.
Familiarity with statistical methods, systematic literature reviews, and meta-analysis.

Responsibilities

Design an end-to-end data pipeline to optimize evidence management, synthesis, and generation processes.
Implement and automate publication search and deduplication strategies.
Assist in integrating additional LLM workflows into the system.
Collaborate with cross-functional stakeholders to develop the solution.
Present and interpret findings to teams across the organization.