ML Research Engineer, Performance Optimization

Summary by AIEngineer.careers

ML Research Engineer, Performance Optimization is a ML Research Engineer role (full-time). with Lilasciences. in CAMBRIDGE, US. Compensation shown: $148K–$240K. Imported from Greenhouse-hosted careers page. Apply on the employer's site (job-boards.greenhouse.io).

Imported from Greenhouse-hosted careers page · Apply on job-boards.greenhouse.io

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CAMBRIDGE · US

$148K–$240K

Full-time

MID

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Imported job description

Sourced from job-boards.greenhouse.io

Lilasciences is hiring an ML Research Engineer focused on maximizing iteration speed for training runs on 1T+ parameter LLMs using NVIDIA chips. The role sits at the intersection of large-scale model training and performance optimization, driving efficiency gains for frontier-scale training workloads.

Responsibilities

Optimize iteration speed for training runs on 1T+ parameter LLMs
Improve performance of large-scale training on NVIDIA hardware
Profile and eliminate training bottlenecks across the stack
Collaborate with research and infrastructure teams on training efficiency

Requirements

BS/MS with 4 years of relevant experience, or PhD with 1 year of experience
Experience with large-scale LLM training
Strong background in performance optimization on NVIDIA GPUs

Nice to Have

Experience with distributed training frameworks
Familiarity with frontier-scale model training

Tech Stack

Distributed TrainingLLM TrainingNVIDIA GPUsPerformance Optimization

Lilasciences

Cambridge · US · 567+ employees

Lila Sciences is the world's first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. Founded in 2022/2023 out of Flagship Pioneering's labs, the company is building AI systems to conduct every step of the scientific method, enabling scientists to bring forth solutions in human health and sustainability at unprecedented pace and scale.