We are looking for a research engineer with strong ML and Generative modeling skills who can define project goals work with cross-functional partners learn quickly and implement and demonstrate new user experiences using large Foundation models. You will build novel and innovative technology forge collaborations and influence multi-functional partners and adapt and iterate your solutions in a dynamic will be expected to advance human interaction modeling across various fronts at a system level and at a core ML algorithm level. Some of the myriad challenges include perceiving subtle cues in gaze affect or prosody handling deeply interleaved streaming inputs reasoning over varying temporal contexts developing memory systems to enable long-term adaptation generating semantically rich internal representations to enable open-ended downstream tasks etc. You will be responsible for delivering solutions that can readily be adopted in production pipelines such as APIs for production-ready ML models or algorithms well integrated into training infrastructure.
PhD or MS in Computer Science Engineering or a related field with a focus on machine learning; or equivalent experience
Proven experience building and deploying large ML models
Expert-level knowledge of SOTA in large auto-regressive transformer models multi-modal encoders and representation learning.
Strong research skills with publications in top tier ML conferences
Experience working with large cross-functional and diverse teams.
Strong programming skills in Python maintaining ML code bases grounded in software engineering principles.
Experience with multimodal large language models (LLMs).
Proven track record of deploying innovative ML technologies in production.
Familiarity with developing ML for resource-constrained devices.
Publications in peer-reviewed venues in relevant areas.
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