Machine Learning Scientist
July 2
🏢 In-office - Bay Area
Description
• Optimize and deploy large-scale deep learning models for protein sequences and structures • Develop efficient, high-quality code, and data pipelines • Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings • Establish automated processes to continuously evaluate and improve our protein design methodology • Work within a collaborative, fast-paced, and interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company
Requirements
• MS or PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field • 2+ years of industry experience in machine learning infrastructure, pipeline building, distributed training and inference, and deployment • Demonstrated ability in re-implementation of multiple state-of-the-art models from research for comparative analysis • Domain expertise in one or more of the following: language models, variational autoencoders, diffusion models, or graph neural networks • Ability to write clean, performant code and deploy services to cloud compute platforms (GCP, AWS, Azure) including experience with scaling ML Workflows with tools such as Kubernetes and Kubeflow, etc.
Benefits
• A high-growth opportunity with meaningful impact • Competitive compensation package • Health insurance (health/dental/vision) • Generous paid time off (PTO) policy • Commitment to physical and mental well-being • More benefits and perks to be added!
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