What are the responsibilities and job description for the Machine Learning Scientist, LLM Training & Inference Research position at Lila Sciences?
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.
Your Impact at Lila
As a Machine Learning Scientist in LLM Training & Inference Research, you will lead research on how we train and serve large language models for scientific applications.
What You’ll Be Building
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.
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.
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.
Your Impact at Lila
As a Machine Learning Scientist in LLM Training & Inference Research, you will lead research on how we train and serve large language models for scientific applications.
What You’ll Be Building
- Develop and optimize LLM post-training strategies including SFT, RLHF, and RL with verifiers.
- Design test-time compute and efficient inference mechanisms for complex tool use environments.
- Build scalable evaluations for LLM performance on scientific reasoning.
- Explore the limits of frontier LLM based approaches for scientific tasks and quantifying their failure modes.
- Strong background in LLM training and deployment.
- Research experience in scalable compute techniques.
- Publications or contributions to open-source frameworks welcome.
- Experience applying LLMs to scientific or technical data.
- Work in collaborative cross-functional ML environments.
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.
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.