Member of Technical Staff, ML for Biology

We are looking for a Member of Technical Staff who is skilled in computational biology and in machine learning. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. In your role you will evaluate, apply and refine our proprietary generative models with the goal of designing new proteins that are functional in wet lab assays.

Who you are

• You are a scientific programmer. You have worked on notable science simulations or machine learning based projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues.

• You are a successful scientist. You have a PhD (or equivalent industry experience) in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bio/chem engineering, synthetic biology or a related field.

• You are an experienced molecular data analyst. As a data analyst, you use techniques from statistics, molecular dynamics and molecular visualization to generate insights on biomolecular problems.

• You are a skilful developer. You write software that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production-quality code.

• You are an owner. You have a proven track record of delivering successful commercial and / or academic research projects, demonstrated through publications, patents, and/or commercially impactful outcomes, as well as other contributions to the scientific community.

• You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.

• You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.

What sets you apart

• You have experience in protein design and bioinformatics. You have worked on ML-driven projects in biology or conducted large scale bioinformatics analysis.

• You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.

• You have helped scale a young biotech before. You have worked in startups and helped the company grow.

Your Responsibilities

• Evaluate the capabilities of our proprietary generative AI models:

  • Design evaluation strategies and benchmarks to continuously evaluate the performance progress of our models.

  • Lead deep-dives on select biological and therapeutic applications. Use your insights to identify opportunities and risks.

  • Compare our generative models against external technologies.

  • Closely collaborate with machine learners, protein designers, and biologists to ensure the technical and biological relevance of our model evaluations. Feed back results via regular meetings and presentations.

  • Incorporate and automate relevant evaluation strategies into our model training workflows.

• Use your insights to help improve our models:

  • Leverage your analytical results to guide model performance improvements.
    Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.

  • Implement and test ideas for model improvements, including finetuning on our own wet lab data and new architectural ideas or model features.

• Improve the way we apply our models:

  • Use evaluation metrics to automatically optimize the way we apply our models, e.g. by identifying optimal sampling techniques and hyperparameters.

• Self development:

  • 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 when relevant.

Apply

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 offer 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 we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.