# Research Engineer / Scientist, Post-Training

**Company:** [Letta](https://hotfix.jobs/companies/letta)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Skills:** Python, PyTorch, Sft, Reinforcement Learning, Reward Models, Preference Learning, Fine-Tuning, Synthetic Data, LLMs
**Posted:** 2025-02-04

> Pioneers post-training techniques to enhance LLMs for agentic systems, focusing on tool-use, continuous updates, synthetic data infrastructure, and capability evaluations. Requires Python/PyTorch proficiency, post-training expertise, and proven research impact.

## Job Description

## 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 running 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 (e.g. 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

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