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Senior Machine Learning Research Engineer I/ II, Open-Endedness

Lila Sciences · San Francisco, CA USA

onsitefull-timesenior level

About this role

Your Impact at Lila

We’re seeking a Machine Learning Research Engineer for the Open-Endedness Team with expertise in large model training and optimizing novel algorithms for best results in distributed ML infrastructure. You’ll design and maintain large-scale training systems, optimize performance for large models, and integrate cutting-edge techniques to improve efficiency and throughput.

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.

What You'll Be Building

  • Distributed training infrastructure for LLMs and multi-modal models.
  • Performance optimizations for large-scale model training including training and optimization workflows (SFT, RL, long-context, etc.).
  • Orchestrate frontier and open source LLMs along with complex compute-intensive tool use
  • Scalable pipelines for data preprocessing and experiment orchestration, including tools for efficient data loading, pipeline parallelism, and optimizer tuning.
  • System-level performance benchmarks and debugging utilities.

What You’ll Need to Succeed

  • Proven experience with distributed ML training frameworks (Megatron-LM, TorchTitan, DeepSpeed, Ray).
  • Strong software engineering skills (Python, C++ kernel contributions are a plus).
  • Understanding of large-scale model training techniques.
  • Experience with cloud or HPC environments.

Bonus Points For

  • Prior work with scientific datasets or domain-specific modeling.
  • Contributions to open-source ML frameworks.

About Lila

Lila 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 introducing scientific superintelligence to solve humankind's greatest challenges, 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  www.lila.ai

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

We’re All In

Lila Sciences is 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.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila 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.

Compensation

We offer competitive compensation including bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.

Expected Base Salary Range
$148,000—$240,000 USD

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