Research Engineer, Post-training (all Industry Levels)

Character AI Character AI · AI Frontier · Redwood City, CA +1 · Technical Staff - ML

Research Engineer on the Post-Training team responsible for fine-tuning AI models, optimizing performance, and ensuring quality and efficiency. Works on alignment algorithms, data pipelines, quality signals, and sampling algorithms for large generative models to shape conversational experiences.

What you'd actually do

  1. Develop alignment algorithms and loss functions to improve data sample efficiency.
  2. Write data pipelines to process diverse web data into a format models can ingest.
  3. Identify quality signals to understand our model’s performance in the real world.
  4. Design sampling algorithms to improve serving efficiency of large generative models.

Skills

Required

  • PhD (or equivalent)
  • production-facing and training code
  • Experience working with GPUs (training, serving, debugging)
  • Experience with data pipelines and data infrastructure
  • Strong understanding of modern machine learning techniques (reinforcement learning, transformers, etc)
  • Track-record of exceptional research or creative applied ML projects

Nice to have

  • Experience with product experimentation and A/B testing
  • Experience training large models in a distributed setting
  • Familiarity with ML deployment and orchestration (Kubernetes, Docker, cloud)
  • Publications in relevant academic journals or conferences in the field of machine learning

What the JD emphasized

  • PhD (or equivalent)
  • Track-record of exceptional research or creative applied ML projects

Other signals

  • Post-training
  • fine-tuning
  • alignment algorithms
  • large generative models
  • conversational experience