Senior/Staff AI Scientist – Polytope Bio

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate closely with the technical founder and team to shape and implement the scientific vision.

• Innovate advanced modeling techniques and quickly iterate on fresh concepts.

• Design, execute, and enhance post-training methods that convert high-throughput biological data into direct reward signals for biological language models.

• Build the architecture for model training infrastructure.

• Develop, execute, and troubleshoot models, training loops, and evaluation metrics.

• Work alongside the experimental team to synchronize laboratory measurements with model learning into a unified system.

• Create and publish novel reinforcement learning techniques and generative AI models utilizing datasets from the high-throughput biology platform.

⛳️ Requirements

• A PhD in machine learning, computational biology, or a related discipline, with at least 1-2 years of post-PhD research or industry experience (prominent researchers without a PhD are also encouraged to apply).

• Experience in training models from the ground up, including taking responsibility for actual training runs and troubleshooting.

• Practical experience with generative diffusion models and/or transformer architectures.

• Understanding of contemporary reinforcement learning and preference-optimization techniques for deep learning.

• Proven record of significant research through publications, open-source contributions, deployed models, or similar evidence of impactful results.

• Highly self-motivated with the ability to excel in a close-knit, collaborative early-stage setting.

• Comfort with ambiguity and a strong desire to create something innovative.

• Enthusiasm for tackling challenging problems and the potential to transition into a technical co-founder position.

• Familiarity with biological research areas such as protein modeling, sequence models, structural biology, or related fields.

• Experience in developing and scaling training infrastructure on large GPU clusters.

• Preference for candidates who can work in-person in NYC or the SF Bay Area; remote work may be considered for the right candidate.

• Must be legally authorized to work in the United States.

• Must indicate if future sponsorship will be necessary.

🏝️ Benefits

• Opportunity to transition into a co-founding technical role in a future spinout, dependent on project success and mutual compatibility.

• Authorship of influential open-source datasets, methods, and models.

• Substantial secured runway and dedicated GPU resources.

• Comprehensive benefits package that includes health insurance, a company-sponsored retirement plan, vision, dental, and more.