Machine Learning Scientist
Job Description: Research Scientist - Foundational Large-Scale Models for Biology
We are working with a visionary, tech company that's on a mission to revolutionize biological science through the development of large-scale foundational models. By discovering architectures that scale in both data and parameters, they aim to create generalizable AI solutions for complex biological systems and tasks.
Position: Research Scientist - Foundational Models in Biological Systems
Locations: San Jose, CA or Remote
Type: Full-Time
What You'll Do
Cross-Functional Collaboration: Partner with experts in biology, chemistry, and engineering to deeply understand datasets and real-world use cases; align evaluation metrics with practical applications.
Model Innovation: Design and implement novel model architectures that tackle tasks like complex molecular structure generation, multimodal integration of sequence/graph/structure/function data, and generative property prediction.
Applied Research: Translate cutting-edge ML research (NLP, CV, RL, generative models) into biological workflows, iterating rapidly from concept to prototype to production.
Knowledge Sharing: Stay abreast of the latest advances in AI and computational biology; actively discuss findings and best practices with the team.
Who You Are
Minimum Qualifications:
PhD in Machine Learning, Computational Biology, Computer Science, or a related field, with publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or journals.
Expert in Python and PyTorch, with a track record of driving research projects from ideation through implementation.
Adaptable learner who thrives in fast-paced environments and eagerly adopts new methods.
Excellent problem-solving skills, creative mindset, and passion for tackling challenging, high-impact problems.
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