Senior Research Scientist, Post-Training LLM and DLM
Core
Designing and implementing post-training algorithms for Large Language Models (LLM) and Diffusion Language Models (DLM), while optimizing training pipelines and serving systems for large-scale generative AI.
Role type
Senior Research Scientist (Post-Training LLM/DLM)
Builds
Efficient large-scale training pipelines, serving systems, and evaluation frameworks for foundation models.
Domain
Generative AI, Large Language Models, Distributed Systems
Deliverable
production ML models
Required skills
Post-training algorithms for LLMs/DLMs, distributed computing, systems programming, Python, PyTorch, algorithm design, data structures
Preferred skills
Novel algorithmic/data pipelines for post-training, scaling large distributed systems for deep learning, open-source contributions to LLM infrastructure
Technologies
PyTorch, Python
Responsibilities
Designing and implementing post-training algorithms for LLMs and DLMs, driving efficiency and scalability improvements across training pipelines and serving systems, collaborating with researchers to translate ideas into production-ready implementations, exploring new paradigms for evaluation
Seniority
Senior, hands-on IC
