Job Description

Locations

• San Francisco Bay Area, California, United States

Salary

Skills Required

• design and development of training large scale ML modelsintermediate
• adapting large scale ML modelsintermediate
• deploying large scale ML modelsintermediate
• natural language understandingintermediate
• natural language generationintermediate
• speech generationintermediate
• multimodal generationintermediate
• applied ML researchintermediate
• training large scale language modelsintermediate
• training large scale multimodal modelsintermediate
• distributed backendsintermediate
• deployment of compact neural architecturesintermediate
• transformersintermediate
• learning personalized policiesintermediate
• privacy preserving mannerintermediate
• ensuring model qualityintermediate
• fairness in MLintermediate
• model robustnessintermediate
• enriching conversation understanding capabilitiesintermediate
• LLMintermediate
• multimodal modelsintermediate
• leading projectsintermediate
• hands-on workintermediate
• cross-functional interactionintermediate
• enriching system safety experienceintermediate

Required Qualifications

• 5 - 7+ years experience in Machine Learning and its application to NLP, NLG or Speech (experience, 7 years)
• Hands on experience training LLMs, adapting pre-trained LLMs for downstream tasks & human alignment (experience)
• Experience delivering ML capabilities into great products (experience)
• Proficiency in using ML toolkits, e.g., PyTorch (experience)
• Strong programming skills in Python, C and C++ (experience)

Preferred Qualifications

• JAX (nice to have) (experience)

Responsibilities

• We are seeking a lead scientist candidate with a proven track record in applied ML research who is not only capable of hands-on work but also leading projects. Responsibilities in the role will include training large scale language and multimodal models on distributed backends, deployment of compact neural architectures such as transformers efficiently on device, and learning policies that can be personalized to the user in a privacy preserving manner. Ensuring quality with an emphasis on fairness and model robustness would constitute an important part of the role. You will be interacting very closely with a variety of ML researchers, software engineers, hardware & design teams cross functionally. Your primary responsibilities will center on enriching conversation understanding capabilities through LLM and multimodal models. The user experience initiative would focus on enriching system safety experience.

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