Lila Sciences, Inc. | San Francisco, CA Machine ...

Machine Learning Scientist, Open-Endedness (Level Flexible)San Francisco, CA USALila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducingscientific superintelligence to solve humankind's greatestchallenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at Lila, 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.Lila Sciences is seeking experienced, creative, and talented Machine Learning Scientist (Open-Endedness) across Scientist I/II and Senior 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.Designing, implementing, and modifying generative models (e.g., LLMs, diffusion models, multimodal models) through unconventional pipelines to achieve unconventional behaviorsUnconventional evaluation techniques, including subjective evaluation and the evaluation of interestingnessCreative approaches to investigating, understanding, and visualizing the internal representations of large models, encompassing mechanistic interpretability but also going in new directions beyond itQuality 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.What You’ll Need to SucceedPhD in quantitative disciplines ideal, but will consider self-taught researchers with exceptional achievementsPublications in relevant conferences, such as NeurIPS, ICML, AAAI, ICLR, GECCO, ICCCExpertise in ML frameworks (PyTorch/TensorFlow/Jax); and/or QD algorithm implementation; and/or neuroevolution algorithm implementationExperience in training and deploying ML models on distributed computing services (g. AWS/GCP/Azure, or clusters).Lila Sciences iscommitted 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.A Note to AgenciesLila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.Apply for this job*indicates a required fieldFirst Name *Last Name *Email *Phone *Location (City)Resume/CV *Enter manuallyAccepted file types: pdf, doc, docx, txt, rtfEnter manuallyAccepted file types: pdf, doc, docx, txt, rtfEmploymentTitleSelect...Start date yearEnd date month Select...End date yearCurrent roleWill you now or in the future require sponsorship for employment visa status (e.g., H-1B visa status)? * Select...If you'll require the company to commence ("sponsor") an immigration or work permit case in order to employ you, either now or at some point in the future, then you should select Yes. Otherwise, select No.Do you currently reside within the continental United States? * Select...Are you able to work in the specified job location, or are you willing to relocate for this position? * Select...When are you able to start a new position? * #J-18808-Ljbffr

Created: 2025-09-17