Principal Applied Research Engineer Scientist

What you'll do

• Develop self-improving systems that learn from deployment signals and optimize performance autonomously in real-world environments.
• Design and operationalize agentic memory frameworks to enable long-horizon reasoning and contextual continuity.
• Architect autonomous multi-agent systems capable of task decomposition, tool use, and dynamic collaboration.
• Translate foundational machine learning research into validated user experiences and production-ready architectures.
• Lead rapid prototyping to move advanced AI concepts into scalable product features.
• Influence platform strategy and define technical directions for integrated hardware and software systems.
• Optimize large language models and multi-modal foundation models for on-device compute constraints.

What we're looking for

• Hold an MSc or PhD in Computer Science, Machine Learning, or a related field.
• Possess equivalent practical experience delivering zero-to-one LLM productization.
• Demonstrate deep expertise in transformer-based LLMs and multi-modal foundation models.
• Show proficiency in integrating text, vision, and audio with cross-modal attention.
• Exhibit hands-on mastery of the model lifecycle including pre-training, fine-tuning, optimization, and safety alignment.
• Possess expertise in designing AI agents for complex reasoning under on-device compute constraints.
• Demonstrate the ability to influence high-level architecture decisions and advocate for research directions.