Research Engineer, ML Systems

About the Role and Team

Joining us as a Research Engineer on the ML Systems team, you’ll be working on cutting-edge ML training and inference systems, optimizing the performance and efficiency of our GPU clusters.
You will develop new technologies to fine-tune leading consumer AI models using a data flywheel, serving 20K+ QPS in production with LLMs.
Your work will contribute to groundbreaking advancements in AI, shaping a future where technology is a companion in our daily lives.

At Character.AI, your talent, creativity, and expertise will not just be valued—they will drive change in an AI-driven world.

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What You'll Do

The ML Systems team is responsible for researching and deploying GPU-efficient systems for AI-enabled products.

As a Research Engineer, you will work across teams and our technical stack to improve training performance and inference runtime, shaping the conversational experience of millions of users daily.

Example Projects:

• Write efficient Triton kernels and optimize them for specific models and hardware
• Develop prefix-aware routing algorithms to enhance serving cache hit rate
• Train and distill LLMs to reduce latency while preserving accuracy and engagement
• Build a scalable distributed RLHF stack powering model innovations
• Develop systems for efficient multimodal (image/video generation) training and inference

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Who You Are

• All Industry Levels: At least PhD (or equivalent) research experience
• Write clear, clean, and production-ready system code
• Strong understanding of modern ML techniques (e.g., reinforcement learning, transformers)
• Proven track record in exceptional research or creative ML systems projects
• Comfortable writing model development code (PyTorch) for training or inference

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