2027 Spring Intern - Data Science & Machine Learning

Genentech•Daly City, CA

6d•Onsite

About The Position

Genentech is seeking a highly motivated Spring Intern to join its Data Science & Machine Learning team and help advance Agentic AI discovery and prototyping. The intern will work at the intersection of Generative AI, software prototyping, and system evaluation, researching, prototyping, and benchmarking agentic AI systems, including question-answering agents and multi-agent evaluation frameworks. A key focus is ensuring these systems are safe, reliable, compliant, and aligned with healthcare standards. The role is based on-site in South San Francisco, California. This is an intensive, paid, 12-week, full-time internship of 40 hours per week, with the possibility of extension to six months or one year. The program begins in January. A location-based stipend is provided. Relocation benefits are not available. The position offers ownership of challenging, business-critical projects and the opportunity to work with biotechnology industry colleagues.

Requirements

Must be currently enrolled in a master's or PhD program.
Must be pursuing a degree in Computer Science, Data Science, AI/ML, Biomedical Informatics, or a related quantitative field.
Foundational proficiency in Python and software development best practices, including version control/Git and writing modular code.
Understanding of Large Language Models and core Generative AI patterns, such as prompt engineering, agentic workflows, or Retrieval-Augmented Generation.
Awareness of AI safety principles, output reliability, and the importance of compliance in high-stakes environments such as biotechnology and healthcare.

Nice To Haves

Excellent communication, collaboration, and interpersonal skills.
Alignment with Genentech's culture and its guiding standards: Integrity, Courage, and Passion.
Academic projects or coursework involving LLM API integration or open-source AI frameworks such as LangChain or LlamaIndex, or experience building with commercial or open-source APIs.
Experience or strong interest in system evaluation, benchmarking, or testing, such as creating test cases, evaluating model accuracy or consistency, or unit testing agent steps.
Strong analytical problem-solving skills, curiosity, and eagerness to experiment in a fast-paced environment.

Responsibilities

Build, test, and refine functional AI agent workflow prototypes for interactive question-answering, search, and workflow automation.
Design and implement a general-purpose evaluation framework to benchmark LLM outputs, agent reliability, tool calling, and reasoning accuracy.
Explore and implement guardrails to make AI agent outputs safe, resistant to hallucinations, compliant with regulatory standards, and consistent with patient safety and privacy guidelines.
Develop clean, maintainable Python code to integrate LLMs with internal APIs, search tools, and structured data sources.
Collaborate with engineers, data scientists, and domain stakeholders to gather requirements, incorporate feedback, and demonstrate prototype capabilities.
Present project findings, system architectures, and evaluation metrics to the broader team at the end of the internship.