Research Engineer / Scientist, Post-Training
LettaAI Agents company
San Francisco, United StatesSenior
Felicis Ventures
Essence VC
Sunflower Capital
Jeff Dean
Clem Delangue
Cristobal Valenzuela
Data & AI
About the role
TL;DR
Pioneer post-training techniques for LLMs in agentic systems.
- •You will pioneer post-training techniques that improve how well LLMs can be integrated into complete agentic systems.
- •Key Responsibilities Training models for better agentic tool-use, particularly for context management Designing mechanisms for continuous model weight updates post-deployment without catastrophic forgetting Designing and run experiments to improve understanding of the interplay between data mixtures, training algorithms, and models Building infrastructure for generating and collecting synthetic data at scale Building challenging evals for measuring agentic capabilities Requirements Proficiency in python and deep learning frameworks eg.
- •PyTorch Expertise in post-training techniques e.g.
- •SFT fine-tuning, reinforcement learning, reward models, preference learning Ability to balance execution speed with empirical rigor Proven track record of impactful research (breakthrough publications and/or open-source contributions) Real-world impact beyond pure academic work
Required skills
PythonPyTorch
Domain expertise
ai
Tech stack
PythonPyTorch