Software Engineer

We are looking for a highly skilled Software Engineer to build the robust, scalable infrastructure powering our biology platform. 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 and maintain the systems that process complex biological data, serve machine learning models, and ensure reliable platform performance at scale.

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.

• You are a backend specialist with deep expertise in architecting distributed applications.

• You have a solid understanding of Python and hands-on experience with Kubernetes and AWS services

• You understand web and service authentication, security best practices, and building secure APIs

• You have solid knowledge of HTTP protocols, REST APIs, and websockets for real-time communication

• You're experienced in database management, from design to optimization.

• MLOps and model serving expertise: You have experience with ML serving infrastructure and understand the unique challenges of serving machine learning models at scale

• High-performance computing: You understand the computational demands of biological and scientific workloads

• Data pipeline architecture: You've built robust data processing pipelines for large-scale scientific data

• Cloud infrastructure: Deep experience with AWS services and cloud-native application development

• Scientific computing background: Familiarity with the computational requirements of biological research and protein analysis

• Backend architecture: Develop and own all backend components of our platform, ensuring scalability and reliability

• Database mastery: Own and manage all aspects of our databases, from schema design to optimization, warehousing, and analytics

• Performance optimization: Optimize performance across the entire backend, ensuring efficient messaging, database queries, caches and horizontal scaling.

• Infrastructure management: Deploy and maintain distributed applications in Kubernetes and AWS

• System reliability: Write scalable and fault tolerant applications. Ensure reliability through comprehensive tests

• DevOps collaboration: Work closely with DevOps teams on deployments and infrastructure management

• Ensuring observability at scale: Instrument complex distributed applications to allow real-time monitoring, debugging, and performance optimization across microservices, enabling rapid incident detection and resolution

• Technical debt management: Address technical debt and refactor code for long-term maintainability

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.