Application Guide

How to Apply for Principal AI Scientist (Polytope Bio)

at Astera

🏢 About Astera

Astera is at the forefront of integrating AI with biology, aiming to revolutionize drug discovery and biological research. Their Polytope Bio initiative leverages advanced machine learning to decode biological data, offering a unique opportunity to work at the intersection of cutting-edge AI and life sciences. Joining Astera means contributing to a mission that could transform how we understand and treat diseases.

About This Role

As Principal AI Scientist, you will co-lead the research program, shaping the scientific vision and technical execution. Your focus will be on developing reinforcement learning feedback loops that translate high-throughput biological measurements into rewards for biological language models, bridging the gap between computational predictions and experimental validation. This role is pivotal in creating a cohesive system that drives innovation in biological AI.

💡 A Day in the Life

Your day might start with a stand-up with your research team to discuss progress on training runs and experiments. You'll likely spend time designing reward functions, debugging model training, and collaborating with wet-lab scientists to refine data collection. Afternoons could involve mentoring junior researchers, reviewing results, and planning next steps, with a mix of deep coding sessions and strategic discussions.

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🎯 Who Astera Is Looking For

  • PhD in machine learning, computational biology, or related field with 2-5 years of industry research experience, or equivalent practical experience.
  • Proven track record of training large-scale models from scratch, including owning and debugging training runs.
  • Hands-on expertise with generative diffusion models and/or transformer architectures, with a deep understanding of their inner workings.
  • Strong familiarity with modern reinforcement learning and preference-optimization methods (e.g., RLHF, DPO, PPO) and their application to language models.

📝 Tips for Applying to Astera

1

Tailor your resume to highlight specific projects where you trained models from scratch, including details on architecture, data, and debugging challenges.

2

In your cover letter, explicitly connect your experience with RL and biological data to the role's requirements, mentioning how you would design reward signals from biological measurements.

3

Showcase any experience you have collaborating with wet-lab scientists or working in interdisciplinary teams, as bridging dry/wet lab is crucial.

4

Include links to your GitHub, papers, or blog posts that demonstrate your hands-on engineering skills and deep understanding of model training.

5

Research Astera's recent publications and products (e.g., Polytope Bio) and mention them in your application to show genuine interest and alignment.

✉️ What to Emphasize in Your Cover Letter

['Your vision for how reinforcement learning can be used to improve biological language models, with concrete examples from your past work.', 'Your ability to lead a research program and mentor junior scientists, highlighting any leadership roles or collaborative projects.', 'Your experience in building robust training infrastructure and debugging complex models, emphasizing your engineering mindset.', "Your enthusiasm for working at the intersection of AI and biology, and how your skills align with Astera's mission."]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read Astera's recent blog posts and papers on Polytope Bio to understand their current approaches and challenges.
  • → Explore the company's website and LinkedIn to learn about their team culture and recent milestones.
  • → Look into their funding, partnerships, and any press releases to gauge the company's growth and strategic direction.
  • → Investigate the specific biological language models they use or have developed, such as those based on DNA/RNA sequences.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you design a reward function from high-throughput biological data (e.g., CRISPR screens, microscopy) to fine-tune a biological language model?
2 Describe a challenging training run you debugged: what was the issue, how did you diagnose it, and what was the outcome?
3 Discuss your experience with diffusion models vs. transformers for biological sequences. What are the trade-offs?
4 How would you approach a scenario where the wet-lab results contradict your model's predictions?
5 What are the latest advancements in RLHF and preference optimization, and how might they apply to biological data?
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⚠️ Common Mistakes to Avoid

  • Submitting a generic cover letter that doesn't mention Astera or the specific role's focus on RL and biology.
  • Overemphasizing theoretical knowledge without demonstrating hands-on experience with model training and debugging.
  • Ignoring the wet-lab collaboration aspect; failing to show you can work effectively with experimental scientists.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

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Good luck with your application to Astera!

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