Member of Technical Staff

We are looking for a highly skilled machine learning researcher with significant experience in generative modeling. 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. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.

• You are a strong ML researcher with experience in generative modeling, having led or worked on notable machine learning projects, documented by contributions to widely used open‑source libraries, significant product launches, or high‑impact publications at venues such as NeurIPS, ICML, ICLR, or Nature.
• You are a skillful ML developer: you write robust, tested, and maintainable ML code, use version control and code review systems, prototype rapidly, and run training and inference on cloud hardware, parallelizing data and models across accelerators.
• You are a data engineer who builds ML data pipelines for training and evaluating deep‑learning models, analytically constructs dataset splits, and builds scalable pipelines.
• You are passionate about model performance, with an intricate understanding of how ML libraries interact with hardware and data, and you optimize deep‑learning models for training and inference speed.
• You are mission‑driven and curious, motivated by a positive impact on patients and customers, adaptable to dynamic environments, and thrive in fast‑paced settings where goals must be achieved efficiently.

• Experience in computational biology or protein design, specifically ML‑driven projects in biology.
• A natural science background with academic training in physics, biology, chemistry, or related fields.

• Build machine learning models that work in the physical world (~90% of your time):
  • Contribute to a careful curation of training and evaluation data.
  • Propose and build ML evaluation metrics that align with real‑world success and company goals.
  • Rapidly prototype generative models against lead metrics and perform deep analyses of improvements.
  • Collaborate in a joint codebase with research scientists, engineers, and protein designers, maintaining highest code standards.
  • Contribute to the maintenance of compute and ML development infrastructure.
  • Plan wet‑lab testing campaigns with the bio team and carry out model inference against biological targets to enable wet‑lab testing.
  • Learn from wet‑lab results and feedback data to refine models.
• Self‑development (~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 internal reading groups.
  • Attend and present at conferences.

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

We offer strongly competitive compensation and benefits packages, and the opportunity to shape the future of synthetic biology through 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.