Research Engineer / Scientist, Post-Training
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.
About the job
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
Skills
Python, PyTorch, Sft, Reinforcement Learning, Reward Models, Preference Learning, Fine-Tuning, Synthetic Data, LLMs
Similar jobs
ML Engineering jobs
Thinking Machines Lab
San Francisco, CA
Build and operate the engineering systems that support post-training research, including reinforcement learning infrastructure, sandboxed execution, data pipelines, and agent scaffolding. The role requires strong Python and systems engineering skills, project ownership, and a relevant bachelor’s degree or equivalent experience.
OpenAI
San Francisco, CA
Build research infrastructure and tooling that enables AI models to design silicon, including reinforcement learning environments, EDA integrations, evaluations, and experiment workflows. The role requires strong software engineering fundamentals and comfort working across research, tooling, and chip-design systems.
Rollstack
United StatesBuild production AI capabilities for automated slide and document generation, working across LLM applications, data analysis, and content generation. The role requires 3+ years in machine learning and NLP, advanced Python, and experience with LLM frameworks and production systems.
ClickUp
United States
Build and operate large-scale ranking and retrieval systems that power search relevance, including hybrid lexical/vector search, embeddings, query understanding, and permission-aware retrieval. Requires a bachelor's degree and 5+ years of ML engineering experience in ranking or information retrieval.
PathAI
Boston, MADevelop and deploy machine learning models for biomedical research and AI products, collaborating with scientific, engineering, and product teams. Requires an advanced quantitative degree, substantial ML experience, Python proficiency, and experience bringing models into production or research applications.