Research Engineer, Post-Training (All Industry Levels)

Key Skills

Algorithms, Apache Beam, GPUs, Machine learning techniques, PyTorch, SPARK Programming, TensorFlow

Job Description

About the role

The Post-Training team is responsible for developing our powerful pretrained language models into intelligent, engaging, and aligned products.

As a Post-Training Researcher, you will work across teams and our technical stack to improve our model performance and training methods, including data, compute and algorithms. You will get to shape the conversational experience of millions of users per day.

Example projects:

• Develop alignment algorithms and loss functions to improve data sample efficiency.

• Write data pipelines to process diverse web data into a format models can ingest.

• Identify quality signals to understand our model’s performance in the real world.

• Design sampling algorithms to improve serving efficiency of large generative models.

Job Requirements

• "All Industry Levels": at least PhD (or equivalent) research experience

• Write clear and clean 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

About Character.AI

Founded in 2021, Character is a leading AI company offering personalized experiences through customizable AI 'Characters.' As one of the most widely used AI platforms worldwide, Character enables users to interact with AI tailored to their unique needs and preferences.