ML Systems & Performance Engineer

You’ll be among the first ML Systems Engineer, joining a team of machine learning researchers and performance engineers in building our personalization and continual learning API, which powers models and agents that learn from user context.

This role is focused on designing, optimizing, and scaling training and inference workloads —bridging the gap between cutting-edge AI research and production. This includes:

• Designing and executing new frameworks, techniques, and systems to improve performance, reliability, latency, and efficiency.
• Partner closely with researchers, turning prototypes into systems that run at scale and feeding systems constraints back into research decisions.
• Optimize serving paths for personalization and memory retrieval, where per-user state and low latency both matter.
• Work on distributed training – data and model parallelism, communication scheduling, and scaling efficiency across multiple GPUs and nodes.