The Opportunity
We are seeking a highly motivated and collaborative Senior/Principal Machine Learning Scientist to join the Perturbation Biology group in the Department of AI for Biology & Translation (AIBT) in Genentech Research and Early Development (gRED). The successful candidate will develop the next generation of machine learning models to derive actionable insights from large-scale high-content perturbation experiments for target and drug discovery. This role requires a deep understanding of machine learning applied to sequencing-based perturbation data, a passion for innovation and inter-disciplinary research, and a commitment to improving healthcare outcomes through cutting-edge technology. We are looking for exceptional researchers with a proven ability to develop and implement research ideas. The candidate is expected to lead high profile projects in collaboration with our therapeutic area leads, and to routinely publish work in top-tier machine learning and scientific venues.
In this role, you will:
Design and apply predictive machine learning algorithms for lab-in-the-loop perturbation screens for drug and target identification.
Work on and integrate a variety of different data modalities such as molecular structures, omics data, images, and text.
Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.
Build and scale machine learning techniques to massive datasets and aid in the deployment of novel machine learning algorithms.
Publish in top-tier machine learning venues and/or scientific journals, present results at internal and external scientific venues, conferences, and workshops.
Who you are
Educational Background: PhD degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.g., Chemistry, Biology) with a strong quantitative focus
Experience:
Senior ML Scientist 0-2 years of experience post PhD, Principal ML Scientist 2-7 years of experience post PhD
Proven track record of developing and applying advanced machine learning models in a research or industry setting.
Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.
Technical Skills:
Proficiency in scientific programming in Python.
Extensive experience with Machine Learning frameworks and libraries (e.g., PyTorch, JAX, Tensorflow).
Strong background in statistics, probabilistic modeling and data analysis.
Soft Skills: Excellent communication, collaboration, and problem-solving skills.
Publications: Strong publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.
Preferred
Practical experience in one or more of the following areas:
Predictive modeling of perturbation datasets to drive experimental design
Predictive modeling and/or generative modeling on molecules and other chemistry applications
Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data
Relocation benefits are NOT available for this job posting.
The expected salary range for this position, based on the location of California, is $147,800 - 274,400 for the Senior ML Scientist, and $172,400 - 320,200 for the Principal ML Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
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