Research Engineer, Post-Training (All Industry Levels)
Core
Developing alignment algorithms, loss functions, and data pipelines to fine-tune and optimize large generative AI models for conversational experiences.
Role type
Research Engineer (Post-Training)
Builds
Fine-tuned AI models and training infrastructure for conversational agents
Domain
Artificial Intelligence / Machine Learning
Deliverable
production ML models
Required skills
alignment algorithms, loss function design, data pipeline engineering, GPU training and debugging, modern machine learning techniques (reinforcement learning, transformers), distributed model training
Preferred skills
product experimentation and A/B testing, ML deployment and orchestration (Kubernetes, Docker, cloud), academic publications in machine learning
Technologies
GPUs, Kubernetes, Docker, cloud platforms
Responsibilities
Develop alignment algorithms and loss functions to improve data sample efficiency; Write data pipelines to process diverse web data; Identify quality signals to understand model performance; Design sampling algorithms to improve serving efficiency
Seniority
All Industry Levels (PhD or equivalent required)
