Applied LLM Experience: Prior success building and scaling systems centered around Large Language Models
ML Infrastructure: Experience setting up the underlying hardware or orchestration for ML systems
GCP: Prior experience building and deploying systems on Google Cloud (GCP)
Scientific Domain: Interest or experience in biology, chemistry, or drug discovery; an interest in applying AI to scientific discovery
Fast-Moving Tooling: Familiarity with the latest in agentic tooling and developer frameworks
Culture and values
We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it
Thoughtful
Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day
Brave
Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less
Determined
Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we
Together
Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere
Creating an extraordinary company
We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact
Hybrid working
It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call
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Software Engineering: Strong coding skills (Python) with a focus on production-grade, maintainable systems
System Design: Ability to architect and maintain (IaC) complex systems across multiple verticals (Security, UX, and Scalability) in the cloud
LLM Internals: Deep understanding of how models are trained, how they work internally, and their inherent limitations
LLM Serving stack: Experience with the LLM serving stack (e.g. vLLM) for open weight models for bringing the latest models to internal users
ML Literacy: Experience evaluating probabilistic ML systems and managing model "tool use", contexts and loops
First-Principles Thinking: A hype-detached approach to solving problems and selecting the right tech stack
Communication: Excellent stakeholder management and the ability to explain technical risks to non-experts