What You'll Do

• 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.

Who You Are

• "All Industry Levels": have at least PhD (or equivalent)
• 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 Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventure s. In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach.

Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!

At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.