Job Details

Machine Learning Engineers (Open-Endedness) - Open Level

Company Summary

Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Lila Sciences is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Join our mission-driven team and contribute to the future of science.

We are leveraging AI across both Life Sciences and Physical Sciences to transform the process of invention and discovery.

At Lila Sciences, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you'd love to work in, even if you only have some of the experience listed below, please apply.

The Role

Lila Sciences is seeking experienced, creative, and talented Machine Learning Engineers (Open-Endedness) across Engineer, Senior Engineer, and Principal Engineer levels to join our team. Title will be determined by merit and experience level.

Open-Endedness is an emerging area of machine learning that aims to automate never-ending innovative processes of discovery and exploration. The Open-Endedness Team, led by Ken Stanley, investigates in particular how a continual chain of deep transformative creativity can be maintained that far exceeds the derivative creativity seen in current models. In effect, the systems developed on this team will go beyond simply solving problems posed by users, to conceiving the future unimagined directions of science itself.

To realize this vision and to facilitate daring and unconventional investigations, we're seeking ML pros skilled in large-scale generative models, data pipelines, and software engineering excellence.

Candidates should have experience and/or interest in:

• Designing data pipelines for machine learning on multi-node GPU clusters
• Training large language models including domain adaptation and retrieval-augmented generation (RAG) as part of an agentic framework
• Implementing robust evaluation frameworks, including custom benchmarks, to rigorously test model performance and reliability
• Integrating ML solutions into production environments

Qualifications:

• Master's or PhD degree in a quantitative field (e.g., Computer Science, Machine Learning, Statistics, Physics, Mathematics) or equivalent industry experience
• Strong background in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX)
• Experience with distributed computing platforms (AWS, GCP, Azure, or on-prem clusters)

Ideal:

• Kubernetes and Docker experience for scalable, reproducible workflows

Working at Lila, you would have access to advanced technology in the areas of:

• AI experimental design and simulation
• Automated custom instrumentation
• Generative molecular and material design

Flagship Pioneering and Equal Employment Opportunity

Flagship Pioneering and our ecosystem companies are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.