The Position
2026 Summer Intern - Translational Pharmacokinetics/Pharmacodynamics
Department Summary
This intern position is in the Translational Pharmacokinetics & Pharmacodynamics (tPKPD) Department within Development Sciences. The tPKPD department applies preclinical models (in silico, in vitro, or in vivo) to determine the pharmacokinetics (what the body does to the drug) and/or pharmacodynamics (what the drug does to the body) of therapeutics. The information obtained from such work is often used to help inform the selection of lead molecules, optimize dosing regimens, and understand the PK behavior of different molecular designs as we help advance molecules through stages of research and into early clinical development. The work within the tPKPD department spans a wide range of disease areas, including oncology, immunology, ophthalmology, infectious disease, and neuroscience.
This internship position is located in South San Francisco, on-site **.
The Opportunity
The Mission:** Build the AI Agents that Build the Models. Join Genentech's Modeling and Simulation group to work at the bleeding edge of Generative AI and Systems Pharmacology . While QSP models are essential for clinical trial design and dosing strategies, their development is currently limited by human coding speed. We are changing that. We are developing a novel Agentic Framework capable of reasoning through hypothesized biology and generating complex mechanistic model code automatically. As an intern, you will deploy Large Language Models (LLMs) to solve real-world problems in drug discovery, moving beyond simple prompting to building autonomous scientific software engineers.
Key Responsibilities:
Architect Advanced Agentic Workflows: Engineer and extend a proprietary multi-agent framework designed to translate natural language into executable mechanistic code. You will focus on improving the agent's reasoning capabilities, @context retrieval, and code generation accuracy.
Rigorous Benchmarking & Validation : Design a robust evaluation framework to stress-test the AI agents. You will validate generated QSP models against ground-truth data and historical case studies, quantifying the system's ability to handle complex therapeutic modalities and ensuring mathematical correctness.
Tool Democratization & Deployment: Bridge the gap between proto@type and product. You will design and deploy intuitive, scalable interfaces (e.g., Dash/Streamlit web apps) that allow M&S scientists to leverage these AI agents in their daily workflows.
Scientific Impact & Collaboration: Act as a bridge between fields. You will present your findings to cross-functional teams, synthesizing feedback to refine the agents and demonstrating how autonomous modeling can directly accelerate Genentech's drug development pipeline.
Program Highlights
Intensive 12-weeks, full-time (40 hours per week) paid internship.
Program start dates are in May/June 2026.
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:
Must be pursuing a PhD (enrolled student).
Required Majors: Scientific Computing, Computer Science, Bioinformatics, Chemical Engineering, Applied Mathematics, or related fields with a strong focus on computational modeling.
Required Skills:
Advanced Agentic Systems: Demonstrated experience architecting and building multi-agent systems. You should have deep working knowledge of orchestration frameworks (LangGraph, AutoGen, or similar), managing graph state, memory persistence, and implementing complex tool-calling/function-calling logic.
Core Engineering & Python: Elite proficiency in Python with a strong grasp of software engineering best practices (version control/Git, modular code design, testing). You are not just scripting; you are building robust software.
LLM Frameworks: Practical experience working with LLM APIs (OpenAI, Anthropic) and integration libraries (LangChain, LlamaIndex). You understand the nuances of prompt engineering vs. fine-tuning vs. RAG.
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.
Reinforcement Learning: Understanding of RL techniques or self-correction loops to optimize agent performance.
Full-Stack Prototyping: Experience building interactive front-ends to showcase your models (e.g., Streamlit, Dash, React) so stakeholders can interact with your agents.
Translation Skills: The ability to explain complex AI architectures to non-coding scientific stakeholders.
Autonomy: Comfort working in an ambiguous, fast-paced environment where the technology stack (e.g., agent frameworks) is evolving rapidly.
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) .
