Responsibilities

• Build machine learning models that work in the physical world (approximately 90% of your time):

  • Contribute to the careful curation of our training and evaluation data.
  • Propose and build ML evaluation metrics that align with real-world success and company goals.
  • Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.
  • Collaborate in a joint codebase with other research scientists, engineers, and protein designers, maintaining the highest code standards.
  • Contribute to the maintenance of our compute and ML development infrastructure.
  • In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.
  • Quickly learn from wet lab results and provide feedback data to our models.

• Self-development (approximately 10% of your time):

  • Stay on top of the latest developments in ML.
  • Gain a strong working understanding of protein and cell biology.
  • Participate in knowledge sharing, e.g., organize and present at our internal reading group.
  • Attend and present at conferences.

Qualifications

• Strong ML researcher with experience in generative modeling.
• Proven track record of deep expertise in generative modeling.
• Experience leading or working on notable machine learning projects.
• Skillful ML developer with robust, tested, and maintainable code.
• Experience using version control and code review systems.
• Data engineer with experience building ML data pipelines for training and evaluation.
• Passionate about model performance and optimization of deep learning models.
• Mission-driven and curious, motivated by making a positive impact.
• Thrives in a dynamic, fast-paced environment.

What Sets You Apart

• Experience in computational biology or protein design.
• Natural science background, academically trained in physics, biology, chemistry, or related fields.

Benefits

We offer strongly competitive compensation and benefits packages, including:

• Private health insurance
• Pension/401(K) contributions
• Generous leave policies (including gender-neutral parental leave)
• Hybrid working
• Travel opportunities and more

We also provide a stimulating work environment and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models. We welcome applicants from all backgrounds and are committed to building a team that represents a variety of backgrounds, perspectives, and skills.