Description
We are seeking a Principal Applied Research Engineer to drive breakthrough innovation across self-improving systems, agentic memory, and deeply personalized autonomous multi-agent systems. You will shape next-generation intelligent architectures that learn continuously, retain and reason over persistent memory, coordinate across agents, and translate frontier research into scalable product experiences. This unique opportunity places you at the forefront of innovation, working on projects that redefine user experiences through advanced machine learning.
Minimum Qualifications
MSc or PhD in Computer Science, Machine Learning, or related field; or equivalent practical experience delivering zero-to-one LLM productization. Deep expertise in transformer-based LLMs and multi-modal foundation models, with a focus on integrating text, vision, and audio with cross-modal attention. Hands-on mastery across the model lifecycle, including pre-training, fine-tuning, performance optimization, and safety alignment. Expertise in designing AI agents for complex reasoning while navigating the unique challenges of on-device compute constraints.
Preferred Qualifications
Demonstrated ability to influence high-level architecture decisions and effectively advocate for novel research directions to product leadership.
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