2025 Summer Intern - Product Development Digital Strategy and Enablement Artificial Intelligence

2025 Summer Intern - Product Development Digital Strategy and Enablement Artificial Intelligence

Department Summary

In DSE we focus on delivering technology that evolves the practice of medicine and helps patients live longer, better lives. We are a diverse team of open and friendly people, enthusiastic about technological novelties and optimal enterprise solutions. We share knowledge, experience & appreciate different points of view. 

This internship position is located in South San Francisco, on-site.

The Opportunity

• Partner with Data Scientists, AI/ML engineers, and cross-functional teams to solve complex problems and create unique solutions using modern NLP technologies, including LLMs.

• Contribute to building data pipelines for ML models.

• Develop and evaluate ML models according to business and functional requirements.

• Document and communicate the design and implementation details.

• Work on accelerating the value of data science and AI across multi-disciplinary teams, specifically focusing on the design, development, and deployment of high-quality AI solutions, with an emphasis on Large Language Model (LLM) solutions.

Program Highlights

• Intensive 12- weeks (possibly being extended to 6 months), full time (40 hours per week) paid internship.

• Program start dates are in May/June (Summer).

• A stipend, based on location, will be provided to help alleviate costs associated with the internship. 

• Ownership of challenging and impactful business-critical projects.

• Work with some of the most talented people in the biotechnology industry.

Who You Are (Required) 

Required Education: You meet the following criteria:

• Must have attained a Bachelor's Degree.

Required Majors: Computer Science, Electronic Engineering, Statistics, Mathematics or other relevant disciplines.

Required Skills

• Solid understanding of Machine Learning fundamentals—especially large language models (LLMs), training objectives, evaluation metrics, and common optimization techniques.

• Familiar with Deep Learning frameworks (TensorFlow, PyTorch, Keras).

• Strong programming skills in Python or another relevant language.

• Experience developing and deploying LLMs in development or production environments.

• Working experience with revision control systems e.g. git.

• Self-learner attitude with software solutions and technologies.

• Curious and eager to engage and learn about various business needs across the organization.

• Ability to work effectively with team members and virtual teams from different locations and different cultural backgrounds. 

Preferred Knowledge, Skills, and Qualifications

• Excellent communication, collaboration, and interpersonal skills.

• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

• Ability to explain complex ideas in a simple, clear way based on the audience.

• Familiarity with cloud / high performance computing clusters environments (Azure, HPC).

• Experience with clinical study data.

• Experience designing or implementing RL algorithms and reward functions (rule-based or otherwise).

• Demonstrated expertise in developing models from scratch and managing the entire deep learning pipeline—including data curation, characterization, and cleaning; architecture design and model building; distributed large-scale training; and model optimization for inference.

Relocation benefits are not available for this job posting. 

The expected salary range for this position based on the primary location of California is $45.00 hour.  Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.

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Genentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.