We are seeking a candidate with a consistent track record in applied ML engineering. Responsibilities in the role will include working with existing data pipelines and annotation teams to collect clean and analyze speech and multimodal datasets. Training large language and multimodal models on distributed back-ends and adapting them for on-device deployment. Ensuring quality with an emphasis on data and model robustness. You will interact closely with other ML researchers software engineers and design teams. Your primary focus will still be enriching conversation understanding through LLM and multimodal modelsnow with added attention to the data that makes these models excel.
57 years experience in Machine Learning applied to Speech & NLP.
Hands-on experience training LLMs adapting pre-trained LLMs for downstream tasks and leveraging curated datasets or human-feedback data.
Familiarity with large-scale data collection/processing (e.g. annotation guidance data quality checks).
Experience delivering ML capabilities into great products.
Proficiency with ML toolkits such as PyTorch.
Strong programming skills in Python and either C or C.
B.S or M.S in Computer Science or equivalent experience
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