Meta is seeking a Research Engineer to develop advanced machine learning models and systems for the Wearable AI Assistant's memory and personalization features, aiming to enhance user experience through multi-modal recall and tailored recommendations.
Requirements
- Proven track record of research in one or more of the following areas: deep learning, information retrieval, personalization, recommendation systems, or LLMs
- 5+ years experience deploying machine learning models and systems at scale in an industry setting
- Demonstrated up-to-date expertise in machine learning research advancements and adherence to industry best practices
- Experience working on wearable or assistant AI technologies
- Expertise in multi-modal machine learning and memory systems
- Demonstrated software engineering capabilities with practical experience in developing and maintaining production machine learning systems
- Proven ability to effectively communicate complex technical concepts
Responsibilities
- Research and develop state-of-the-art machine learning models and novel algorithms tailored to wearable AI assistant capabilities, with a primary focus on memory, personalization, multi-modal recall, and recommendation systems
- Design, prototype, and implement robust systems enabling multi-modal recall of user experiences, integrating a wide range of data sources such as text, audio, image, and sensor inputs for contextual understanding
- Architect and optimize machine learning pipelines for dynamic user personalization and tailored recommendations, ensuring scalable, low-latency performance for real-world applications
- Conduct rigorous experimentation, ablation studies, and evaluation—analyzing model performance using quantitative metrics and qualitative feedback to drive algorithmic improvements
- Monitor, maintain, and iterate on deployed machine learning systems at scale, ensuring reliability, security, and continual enhancement based on user behaviors and emerging platform data
- Stay at the forefront of research and industry trends in deep learning, multi-modal modeling, information retrieval, recommendation, personalization, LLMs, and related disciplines, bringing new methodologies into the team’s research and development pipeline
- Communicate findings and contribute to technical documentation, internal presentations, and external publications where appropriate
Other
- Collaborate closely with product managers, engineers, and UX designers to align technical solutions with user needs and deliver innovative, production-ready features
- Proven ability to effectively communicate complex technical concepts and collaborate productively with cross-functional teams
