Character’s mission is to empower everyone with AGI. Our vision is to enable people with our technology so that they can use Character.AI any moment of any day.
Achieving our mission will require solving ambitious technical challenges, including engineering, research, and design, and we are assembling a world-class team to do so. Our founding team includes AI pioneers from Google Brain and Meta Research whose research has led to major breakthroughs in natural language understanding and dialog applications such as Transformers and Google LaMDA.
Check out our beta to get a glimpse into the future.
Joining us as a Research Engineer on the Post-Training team, you'll be diving into the exciting world of fine-tuning AI models, optimizing their performance, and ensuring they meet the highest standards of quality and efficiency. Your work will directly contribute to our groundbreaking advancements in AI, helping shape an era where technology is not just a tool, but a companion in our daily lives. At Character.AI, your talent, creativity, and expertise will not just be valued—they will be the catalyst for change in an AI-driven future.
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.
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
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
Character is an equal opportunity employer and does not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. We value diversity and encourage applicants from a range of backgrounds to apply.
