2025 Summer Intern - Prescient Design, Large Language Models

Department Summary

Prescient Design is seeking exceptional graduate student interns with a strong research background in machine learning (ML), a passion for independent exploration, and the ability to develop and implement innovative ideas. Ideal candidates excel at conducting independent research, solving complex technical problems, and collaborating effectively within cross-functional teams.

Prescient Design, now an integral part of Genentech's Research and Early Development (gRED) organization, leverages cutting-edge machine learning technologies to revolutionize drug discovery and development. Our team comprises experts in machine learning and computational biology, dedicated to pioneering innovative solutions that expedite the creation of life-saving therapies.

One of Prescient's new, innovative efforts is in developing state-of-the-art large LLMs for scientific discovery and biomedical applications. We envisage LLMs for use across the drug discovery and development pipeline, including applications like scientific document classification to conversational models and multimodal learning of complex data types including biological sequences and high-resolution microscopy images

This internship position is located in New York, on-site.

The Opportunity

As a Machine Learning Engineer Intern in Prescient Design Large Language Models team, you will:

• Work on Post-Training Techniques: Investigate and implement advanced post-training techniques to enhance the performance and efficiency of our internal LLMs.

• Improve Reasoning Capabilities of LLMs: Work on improving the reasoning capabilities of LLMs by integrating them with formal reasoning engines such as logic solvers or symbolic reasoning frameworks.

• Model Training and Fine-Tuning: Assist in training and fine-tuning large LLMs using a high-performance GPU cluster.

• Applied Use Case Analysis: Collaborate with internal teams to design and implement applied use cases for LLMs and reasoning-enhanced models.

Program Highlights

• Intensive 12-weeks, 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 one of the following criteria:

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

Required Majors: Computer Science, Data Science, Machine Learning, Statistics, or a related technical field.

Required Skills:

• Programming Proficiency: Strong programming skills, particularly in Python; experience with machine learning frameworks such as TensorFlow or PyTorch.

• Machine Learning Expertise: Solid understanding of machine learning concepts, including supervised and unsupervised learning, neural networks, and representation learning techniques.

• Communication Skills: Excellent written and verbal communication abilities, with a capacity to work collaboratively in a multidisciplinary team environment.

Preferred Knowledge, Skills, and Qualifications

• Experience with large language models (LLMs) and their development.

• Familiarity with Formal Reasoning: Understanding of formal reasoning engines, knowledge representation, or logic-based AI techniques (e.g., first-order logic, theorem proving, knowledge graphs).

• Experience working with GPU clusters and distributed training systems to scale models efficiently.

• Excellent communication, collaboration, and interpersonal skills.

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

Relocation benefits are not available for this job posting.

The expected salary range for this position based on the primary location of New York is $45-$50 hourly. 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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