Research Scientists & Engineers - Generative AI for Biology

Job Description: Research Scientists & Engineers - Generative AI for Biology & Medicine

We are partnered with a newly established startup where visionary scientists, engineers, and entrepreneurs are redefining the future of biology and medicine through the power of Generative AI. We are building a transformative, interdisciplinary R&D team dedicated to decoding biology holistically and enabling the next generation of life-changing solutions and hiring for individuals at all levels (preference Staff / Principal).

Position: Research Scientists & Engineers - Generative AI for Biology & Medicine
Location: Silicon Valley, CA (with global outreach opportunities)
Type: Full-Time

• Innovative Method Development: Design, implement, and benchmark novel deep learning methods for a range of biological applications. This includes computational protein design, generative modeling, and large-scale biological data analysis.
• Pipeline Engineering: Build, test, and deploy scalable, cloud-based pipelines that drive robust model training, testing, and inference.
• Interdisciplinary Collaboration: Work closely with a diverse team of experts in AI, computational biology, and traditional biological sciences to integrate cutting-edge techniques with complex datasets-ranging from single-cell RNA sequencing to spatial transcriptomics and proteomics.
• Research & Publication: Contribute to high-impact research by publishing findings in top-tier AI/ML and biology journals and conferences, helping to shape the future of biomedicine.
• Cross-Disciplinary Problem Solving: Tackle high-level challenges in drug design, bio-engineering, personalized medicine, and fundamental biomedical research by bridging AI with biological insights.

Essential Qualifications:

• Educational Background: PhD (or evidence of equivalent expertise) in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Bioinformatics, Biochemistry, or a related technical field.
• Proven Innovation: A strong track record in research and innovation, with contributions to top-tier AI/ML (e.g., NeurIPS, ICML, ICLR) and/or core biology (e.g., Nature, Science, Cell) publications.
• Technical Expertise: Proficiency in deep learning frameworks (JAX, TensorFlow, or PyTorch) and programming languages (Python, C/C++, Java). A solid foundation in statistics, optimization, graph algorithms, and linear algebra is essential.
• Hands-On Experience: Demonstrated experience in developing, implementing, and debugging complex models, with a keen interest in generative methods, graph neural networks, or large-scale deep learning applications.
• Interdisciplinary Passion: A drive for bridging AI and biology, with the ability to rapidly learn new domain knowledge in a fast-paced startup environment.
• Engineering Best Practices: Familiarity with version control, documentation, and open-source contributions.

Preferred Qualifications:

• 3+ years of post-PhD industry or postdoctoral experience, ideally in a startup or top-tier research lab environment.
• Experience working with diverse biological datasets (e.g., transcriptomics, epigenetics, proteomics, genetics).
• Familiarity with biological structure prediction algorithms (such as AlphaFold, RosettaFold) and network/systems biology methodologies.
• Expertise in distributed training, ML on accelerators, and cloud services.
• Prior exposure to graph ML frameworks (e.g., PyTorch Geometric, DGL) and advanced generative models.

This is your chance to join a team of dreamers and innovators who are pushing the boundaries of what's possible in biology and medicine. With our global footprint and cutting-edge approach, you'll play a pivotal role in pioneering transformative solutions that impact healthcare on a worldwide scale. If you're ready to leverage your expertise at the intersection of AI and biology to drive revolutionary change, we'd love to hear from you.