• Job Description

  Req#: 32155350361

  Machine Learning Researchers (Open-Endedness) - Open Level

  San Francisco, CA USA

  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 Researchers (Open-Endedness) across Scientist, Senior Scientist, and Principal Scientist 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, we're seeking a broad tapestry of ML expertise to facilitate daring and unconventional investigations, including but not exclusive to pre-training, fine-tuning, RLHF, distillation, mechanistic interpretability, and quality diversity (QD) techniques.

  Candidates should have experience and/or interest in some or all of:

  • Designing, implementing, and modifying generative models (e.g., LLMs, diffusion models, multimodal models) through unconventional pipelines to achieve unconventional behaviors.
  • Unconventional evaluation techniques, including subjective evaluation and the evaluation of interestingness.
  • Creative approaches to investigating, understanding, and visualizing the internal representations of large models, encompassing mechanistic interpretability but also going in new directions beyond it.
  • Quality diversity (QD) algorithms like MAP-Elites, novelty search with local competition, POET, OMNI, minimal criterion novelty search, etc., with LLMs or other large models potentially being updated on the inner loop.

  Qualifications:

  • PhD in quantitative disciplines ideal, but will consider self-taught researchers with exceptional achievements.
  • Publications in relevant conferences, such as NeurIPS, ICML, AAAI, ICLR, GECCO, ICCC.
  • Expertise in ML frameworks (PyTorch/TensorFlow/Jax); and/or QD algorithm implementation; and/or neuroevolution algorithm implementation.
  • Experience in training and deploying ML models on distributed computing services (e.g., AWS/GCP/Azure, or clusters).

  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.

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• About the company

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