Job opening
Computational Protein Design
San Francisco
Machine Learning Full Time
We are seeking a Computational Protein Design Scientist to join our team working at the interface of generative AI and synthetic biology. You will play a key role amongst a team of scientists designing and engineering proteins for specific functions. This is an opportunity to help shape and grow an organization that advances artificial intelligence and applies it to longstanding scientific challenges. Using your blend of computational expertise and in-depth biochemical understanding of proteins, you will generate insights to improve protein functionality and operate at the interface between our machine learning and experimental platform units, working closely to seamlessly integrate AI generations and lab validation data.
Who we are
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind's Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.
We're looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.
Who you are
What sets you apart (preferred but not required)
Your responsibilities
Leverage our proprietary generative AI models to design proteins for experimental validation:
Analyze protein design problems based on functional requirements, biochemistry, structural biology and sequence homology
Generate designs using our proprietary generative AI models and optimize designs for experimental validation
Coordinate with our lab-based protein engineers to plan and optimize the design process and validation strategy
Leverage our proprietary data to improve our models:
Analyze and leverage our experimental results to improve the next round of designs and increase our success rate over validation rounds
Collaborate with machine learning scientists to fine-tune and prompt our models
Collaboration and communication:
Be an effective interface between machine learning model development and experimental validation
Capture bioengineering learnings and feedback to our machine learning unit, and vice versa
Foster a collaborative and innovative environment, proactively finding opportunities to innovate and create clarity and alignment between different units
Contribute to our computational tools:
Help improve the way we use, serve and integrate our AI models, by feeding back to the software engineers and foundational machine learning unit
Help improve our data management systems and workflows
Scientific excellence and self development:
Work to the highest scientific standards (publication-grade work)
Stay on top of relevant developments in synthetic biology
Apply
We offer strongly competitive compensation and benefits packages, including:
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.
To apply, please fill in our application form.