Research Scientist Manager – Generative AI – Llama Pre-training
Company | Meta |
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Location | Menlo Park, CA, USA, New York, NY, USA |
Salary | $177000 – $251000 |
Type | Full-Time |
Degrees | PhD |
Experience Level | Senior |
Requirements
- 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
- Experience and track record of landing large research and/or product impacts in a fast-paced environment
- 3+ years of hands-on supporting and leading teams of research scientists and software engineers
- Proven technical vision in where the field of generative AI will go
- Experience of and knowledge of data curation techniques (training set preparation, ablation experiments, etc.)
- Experience with cross functional collaboration with other teams including non-engineering functions
- Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management
Responsibilities
- Drive end-to-end development of large language models, including data sourcing and curation, filtering, experiment design, evaluation and more
- Drive efficiency gains on training and deployment of LLMs through novel techniques
- Lead a team of applied researchers to democratize Llama for Meta’s users
- Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects
- Remain up-to-date on ongoing research and software development activities in the team, help work through technical challenges, and be involved in design decisions
- Remain involved in the research community, both understanding trends, and setting them
Preferred Qualifications
- PhD in deep learning, artificial intelligence, and/or related technical field
- Experience and knowledge of ML frameworks like PyTorch, TensorFlow, etc.
- Experience and knowledge of large-scale data platforms such as Spark, Hive, etc.
- Experience and knowledge of working with LLM frameworks like LangChain
- Experience and knowledge of training LLMs, fine-tuning on datasets, especially Llama