Application Guide

How to Apply for Research Engineer (Machine Learning)

at Poseidon Research

🏢 About Poseidon Research

Poseidon Research (Genesis) is pioneering molecular AI with GEMS, their AI Operating System for drug discovery. They uniquely combine proprietary AI foundation models like Pearl with physics research to invent cutting-edge medicines at unprecedented speed, making them ideal for engineers passionate about applying machine learning to solve real-world biological challenges.

About This Role

As a Research Engineer (Machine Learning), you'll develop and deploy GEMS, their AI platform for drug discovery, focusing on foundation models like Pearl. You'll work on 3D diffusion models and generative AI to design potent, selective drug candidates, directly impacting Genesis's pipeline and their pharma partners' success.

💡 A Day in the Life

A typical day involves developing and optimizing machine learning models for GEMS, such as enhancing Pearl's 3D diffusion capabilities. You'll collaborate with scientists to integrate AI insights into drug design workflows, run experiments on protein targets, and deploy platform updates to support rapid drug candidate discovery.

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🎯 Who Poseidon Research Is Looking For

  • Strong background in machine learning, especially generative models (e.g., diffusion models, GANs) and 3D data processing, with experience in PyTorch or TensorFlow.
  • Knowledge of computational biology, chemistry, or physics, enabling collaboration with scientists on protein targets and drug design challenges.
  • Proven ability to build and deploy AI systems in research or production environments, with a focus on scalability and performance for drug discovery applications.
  • Passion for AI-driven scientific innovation, with curiosity about molecular structures and a desire to contribute to cutting-edge medicine development.

📝 Tips for Applying to Poseidon Research

1

Highlight specific projects involving generative AI, 3D data (e.g., molecular structures, point clouds), or diffusion models, as these are core to Pearl and GEMS.

2

Emphasize any experience in drug discovery, computational biology, or related fields, even if tangential, to show alignment with Genesis's mission.

3

Tailor your resume to include keywords like 'foundation models,' 'AI platform,' 'deployment,' and 'drug candidates,' mirroring the job description's language.

4

Provide examples of collaborating with scientists or cross-functional teams, as this role involves forward-deployed work with researchers.

5

Include links to GitHub repos or publications showcasing AI research, especially if related to molecular modeling or generative methods.

✉️ What to Emphasize in Your Cover Letter

["Express enthusiasm for Genesis's mission of AI-first drug discovery and mention specific aspects of GEMS or Pearl that excite you.", 'Detail relevant experience with machine learning in scientific contexts, such as prior work on biological data or generative models for 3D structures.', 'Explain how your skills align with building and deploying AI platforms, emphasizing scalability and impact on drug design pipelines.', "Show curiosity about their pipeline or pharma partnerships, indicating you've researched their work and understand its challenges."]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Study Genesis's GEMS platform and Pearl model details from their website or publications to understand their technical approach.
  • → Look into their pipeline and pharma partners to grasp the real-world applications and targets they're addressing.
  • → Review their company blog or news for recent achievements, such as drug candidate discoveries or platform updates.
  • → Research the broader field of AI in drug discovery, including competitors and trends, to contextualize Genesis's work.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Discuss your experience with diffusion models or other generative AI techniques, possibly with coding exercises on 3D data generation.
2 Explore your knowledge of drug discovery processes, such as target identification or molecular design, and how AI can accelerate them.
3 Ask about your approach to deploying AI models in production environments, focusing on scalability and integration with scientific workflows.
4 Inquire about collaboration with scientists, including examples of translating research insights into engineering solutions.
5 Pose scenario-based questions on improving Pearl or GEMS, testing your problem-solving skills in molecular AI contexts.
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⚠️ Common Mistakes to Avoid

  • Submitting a generic application without mentioning GEMS, Pearl, or molecular AI, showing lack of research into Genesis's niche.
  • Overemphasizing generic ML skills without linking them to biological or 3D data applications, missing the role's scientific focus.
  • Failing to demonstrate collaboration experience, as this role requires close work with scientists in a forward-deployed team.

📅 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!

Ready to Apply?

Good luck with your application to Poseidon Research!

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