Principal AI Scientist: Bio-Driven RL Models

Openkrill; United States; Remote; USD 250,000 - 350,000; Full time

Job summary

Astera is seeking a Principal AI Scientist to launch and lead an AI research program at the intersection of frontier ML and high-throughput biology. You will shape scientific direction, modeling approaches, and training strategy with substantial compute and data throughput.

The role offers the potential to grow into co-founding leadership in a future spinout, with residency resources and a strong collaboration with the founder to push the science forward.

Qualifications

• PhD in machine learning, computational biology, or a related field with 2–5 years of industry research post-PhD.
• Trained models from scratch, with hands-on training runs and debugging.
• Experience with generative diffusion models and/or transformer architectures.
• Deep familiarity with modern reinforcement learning and preference-optimization methods.
• Proven track record of research via publications, open-source work, or shipped models.
• Entrepreneurial mindset and ability to work in a founding partnership.

Responsibilities

• Co-direct the research program: Partner with the founder to shape the scientific vision, research direction and execution.
• Develop RL feedback loop: translate high-throughput biological measurements into reward signals for biological language models.
• Hands-on engineering: architect training infra, run and debug models, training loops and evaluation metrics.
• Bridge wet/dry lab: align lab measurements with model learning as a cohesive system.

Skills

Model training from scratch

Reinforcement learning

Generative diffusion / transformers

Builder mindset / research excellence

Entrepreneurial spirit

Education

PhD in machine learning or computational biology

Tools

Large GPU clusters

Training infrastructure

Job description

Astera is seeking a Principal AI Scientist to launch and lead an AI research program at the intersection of frontier ML and high-throughput biology. You will shape scientific direction, modeling approaches, and training strategy with substantial compute and data throughput.

The role offers the potential to grow into co-founding leadership in a future spinout, with residency resources and a strong collaboration with the founder to push the science forward.