Research Engineer

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join Our Team!

As a Research Engineer, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale.

What You'll Do

• Build on and advance the AI systems at the frontier of biology to accelerate science
• Design novel model architectures and scale pre-training pipelines for our biology foundation models.
• Build post-training systems that drive biological discovery: RL, reward modeling, reasoning, and multi-agent orchestration for long-horizon scientific tasks.
• Design evaluation frameworks and AI systems with scientists across Biohub and beyond, grounded in real biological outcomes and real world impact.
• Engage the wider scientific community through impactful publications, open-source releases, and collaborations worldwide.

What You'll Bring

• Significant experience building and scaling deep learning systems, ideally in research-driven environments
• Strong engineering and scientific fundamentals
• Comfort with ambiguity, rapid iteration, and loosely-defined research problems
• Strong communication skills across technical and scientific audiences

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the inter