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Research Engineer, Post-Training (All Industry Levels) — Character.AI

Redwood City, CA · New York, NY · Nghiên cứu AI · Toàn thời gian · $225.000 – $400.000/năm

CUDA / GPUKubernetesLLM / TransformerFine-tuning / RLHFReinforcement learningDockerData pipeline / ETL
Đọc nhanh: Thuộc nhóm Nghiên cứu AI, nơi làm việc Redwood City, CA · New York, NY, lương công bố $225.000 – $400.000/năm (chưa gồm cổ phần/thưởng). Character.AI hiện mở 13 tin, trong đó 0 tin ở châu Á – Thái Bình Dương và 0 tin đặt tại Việt Nam (xem tất cả). Mô tả bên dưới là nguyên văn tiếng Anh do công ty đăng; nộp hồ sơ trên trang gốc.
Ứng tuyển trên trang gốc →Mở trang tuyển dụng của Character.AI. CV Work không nhận hồ sơ cho tin này.

Mô tả công việc (nguyên văn của nhà tuyển dụng)

About the role and team

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.

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 adventures.


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.

Ứng tuyển trên trang gốc →Mở trang tuyển dụng của Character.AI. CV Work không nhận hồ sơ cho tin này.

Vị trí khác tại Character.AI

Nguồn: trang tuyển dụng chính thức của công ty qua hệ thống Ashby. Mô tả giữ nguyên văn của nhà tuyển dụng; ghi nhận lần đầu 2026-08-05, kiểm gần nhất 2026-08-10.