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About the Role
Join a research and engineering team developing benchmarks and evaluation methods for advanced language models. Your work will help AI labs and enterprise teams understand model capabilities and make informed decisions before deploying models in production.
Responsibilities
- Evaluate newly released AI models across a range of capabilities and use cases.
- Build benchmarks from the ground up, including dataset development, labeler coordination, and research publication.
- Develop scalable and accurate methods for automatically evaluating generated text.
- Work with engineering teams to implement evaluation methods in production systems.
- Collaborate with AI labs and enterprise customers to translate evaluation needs into research initiatives.
Requirements
- At least 3 years of full-time AI/ML research experience, particularly in benchmarking, evaluation methods, NLP, or language models; applied experience is valued.
- A record of published research, ideally related to NLP or benchmarking.
- Strong Python skills and experience building clean, maintainable software; familiarity with Django, Flask, or similar Python HTTP frameworks.
- Experience with PyTorch or TensorFlow, language modeling, LLM infrastructure, and relevant deep learning techniques.
- Experience designing benchmarks and translating research findings into practical, scalable systems.
- Experience collaborating on engineering teams, including Git workflows, code review, and incorporating feedback.
Skills
- Python
- Django
- Flask
- PyTorch
- TensorFlow
- Language Modeling
- LLM Infrastructure
- Deep Learning
- Git
Location
- San Francisco, California, United States
Work Type
- On-site
- Full-time
Experience Level
- 3+ years of AI/ML research experience
Education Level
- Master's or PhD preferred
- Bachelor's degree with relevant applied experience may be considered
Salary/Compensations
- $150,000 to $200,000 annually
Benefits
- Visa sponsorship is available.