Research Engineer, LLM Post-Training
Lila Sciences is seeking a Machine Learning Research Engineer specializing in Large Language Model (LLM) post-training to join our team. In this role, you will design and maintain large-scale training systems, optimize performance for massive models, and integrate cutting-edge techniques to improve efficiency and throughput. This position offers the opportunity to contribute to pioneering advancements in scientific superintelligence.
As a Research Engineer, your primary responsibilities will include developing Ray-based distributed training infrastructure for LLMs and multi-modal models, implementing performance optimizations for large-scale model training—including workflows such as Supervised Fine-Tuning (SFT), Mixture of Experts (MoE), and long-context scaling—and orchestrating frontier and open-source LLMs alongside complex, compute-intensive tool usage. Additionally, you will build scalable pipelines for data preprocessing and experiment orchestration, incorporating tools for efficient data loading, pipeline parallelism, and optimizer tuning, as well as system-level performance benchmarks and debugging utilities.
The ideal candidate will have proven experience with distributed machine learning training frameworks such as Megatron-LM, TorchTitan, DeepSpeed, or Ray. Strong software engineering skills in Python are essential, with C++ kernel contributions considered a plus. A solid understanding of large-scale model training techniques and experience with cloud or high-performance computing (HPC) environments are also required.
We offer competitive compensation, including bonus potential and generous early equity. The expected base salary range for this role is between $189,000 and $289,000 USD per year, with the final offer reflecting your unique background, expertise, and impact.
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. Our mission is to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at an unprecedented pace and scale.