About the role
Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.
The Role The Machine Learning team at Profluent has two core objectives: (1) to train increasingly capable models as quickly and reliably as possible, and (2) to build scalable, intuitive systems and software around these models to accelerate protein design. As a Software Engineer on the ML Engineering team, you will contribute directly to both goals. On the research side, you’ll build systems and tools that enable scientists to rapidly prototype ideas, scale complex experiments, and evaluate new models — anything from a distributed job orchestration service to a model evaluation platform. On the design side, you’ll build the infrastructure and software that empower our design team to tackle an increasing number of protein design challenges with greater speed and less friction — the inference stack, model APIs, and design pipelines, for example. Our ideal candidate will have a rigorous engineering background and a strong product mindset. You’ll be responsible for taking projects from user research through systems design through implementation and deployment. As an early member of a small team, you will have significant ownership and the opportunity to shape the technical foundation of our growing engineering organization.
Who You Are: You’re comfortable taking ownership and working independently in a fast-moving environment. You’re an execution-oriented engineer who maintains high standards and focuses on the highest-impact work. You’re comfortable owning the full stack of your work, from system design to implementation to deployment on infrastructure. You care deeply about code quality. You build systems that emphasize efficiency, scalability, and reliability. You’re willing to step beyond your core
