2026 Summer Intern - CSCoE AI for Drug Discovery

Genentech • South San Francisco, CA • 10h ago

The Position

Department Summary

At Genentech Machine Learning Drug Discovery (MLDD), Prescient Design, we are revolutionizing drug discovery with ground breaking machine learning techniques.

The Engineering team within Prescient Design works on applications and infrastructure that make drug discovery R&D possible. One such paradigm is Lab in the Loop (LITL) which connects the in-silico drug discovery with wet lab evaluations about a particular hypothesis about a new drug candidate. We develop and maintain various software related to Lab in the Loop, as well as various methods and models that enable in-silico drug discovery.

We are seeking exceptional interns with a demonstrated background in software development, and a strong interest in implementing novel ideas with efficient and maintainable code. As an intern, you will work alongside engineers and scientists on projects with a real world impact to develop critical software used across Prescient Design, Genentech and Roche.

We are particularly interested in candidates who are enthusiastic about data science and engineering.. A background in biology is advantageous but not required for this role.

This internship position is located onsite in South San Francisco, CA or New York City, NY on-site.

The Opportunity

Design, build, and maintain robust data pipelines (ETL/ELT) to process and integrate large-scale biological and chemical datasets.

Collaborate with engineering and scientific teams to translate research ideas into production-ready software tools and infrastructure.

Optimize existing models and data workflows for performance, scalability, and maintainability.

Design and drive meaningful contributions to existing data platform infrastructure.

Participate in code reviews, contribute to documentation, and present project findings to the team.

Program Highlights

Intensive 12-weeks full-time (40 hours per week) paid internship.

Program start dates are in May 11 or June 1 (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 Education

Must be pursuing a Bachelor's Degree (enrolled student).

Must be pursuing a Master's Degree (enrolled student).

Required Majors

Computer Science

Bioinformatics

Data Science

Statistics

Bioinformatics / Computational Biology

Required Skills:

Strong foundation in machine learning concepts and algorithms.

Proficiency in Python programming (e.g., PyTorch, TensorFlow, scikit-learn).

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.

Preferred: Basic understanding of data engineering principles and data pipelines (e.g., ETL/ELT).

Preferred: Experience working with large biological or chemical datasets (e.g., genomics, proteomics, small molecules).

Preferred: Experience with some database querying language (e.g. SQL)

Relocation benefits are not available for this job posting.

The expected salary range for this position based on the primary location of California is $50.00 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.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants (https://docs.google.com/forms/d/e/1FAIpQLSdZWlsbfQOvFVIQgHE_iDzWUTlhZvj6FytIzjS7xq6IGh1H5g/viewform) .

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