Senior Machine Learning Scientist (gCS, BRAID)

$165,200 - $306,800/Yr

Genentech - South San Francisco, CA

Full-time - Senior

South San Francisco, CA

Chemical Manufacturing

About the position

The Senior Machine Learning Scientist will join the BRAID team within Genentech's Computational Sciences organization, focusing on developing innovative machine-learning methods to enhance drug development and clinical trial design. This role emphasizes the application of advanced machine learning techniques, including multimodal generative models and reinforcement learning, to improve healthcare outcomes. The successful candidate will be expected to publish research findings in top-tier venues and collaborate with cross-functional teams to integrate machine learning solutions into clinical decision-making.

Responsibilities

• Design and implement novel machine learning algorithms tailored to the complexities of clinical trial data.
• Collaborate with cross-functional teams including biologists, clinicians, data scientists, and other stakeholders to integrate machine learning solutions into clinical decision-making.
• Analyze complex biological and clinical data to derive insights and guide decision-making in drug development and trial design.
• Keep abreast of the latest developments in machine learning and their applications in healthcare and clinical trials.
• Publish findings in relevant journals and conferences.

Requirements

• Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field.
• Proven track record with 1+ years of experience developing and applying advanced ML models in a research or industry setting.
• Proficiency in scientific programming languages such as Python and familiarity with MLOps workflows.
• Extensive experience with machine learning frameworks and libraries such as JAX, PyTorch, Tensorflow.
• Strong background in statistics, probabilistic modeling, and data analysis.
• Excellent communication, collaboration, and problem-solving skills.
• Strong publication record and experience contributing to research communities.

Nice-to-haves

• Extensive track record of delivering innovative solutions in machine learning.
• Strong communication skills and ability to effectively communicate technical concepts to both technical and non-technical audiences.
• Practical experience in reinforcement learning, graph neural networks, representation learning, and generative learning.
• Passion for solving complex technical problems and commitment to staying up-to-date with the latest developments in machine learning.

Benefits

• Discretionary annual bonus based on individual and Company performance.