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Research Engineer – Fundamental AI Research – Alignment and AI & Society
| Company | Meta |
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| Location | New York, NY, USA |
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| Salary | $56.25 – $173000 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Mid Level |
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Requirements
- Master’s degree in Computer Science, Computer Engineering, a relevant technical field, or 2+ years of equivalent domain-specific industry experience.
- Experience with Python, C or C++ or other related languages and with the PyTorch framework.
- Development experience in training large-scale AI models and performance evaluation, and familiarity with model architectures such as Large Language Models, Transformers, and Recommender Systems.
- Experience in solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.
- Experience working and communicating cross-functionally in a team environment.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Currently has, or is in the process of obtaining a Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
Responsibilities
- Carry out cutting-edge research to advance the field of machine learning and artificial intelligence.
- Contribute research that leads to innovations in: alignment, personalization, societal and economic impact of artificial intelligence.
- Devise rigorous engineering and data-driven approaches for efficient training of AI models and algorithms implementation.
- Collaborate with research scientists and cross-functional partners in a team environment.
- Publish research results and contribute to research that impacts Meta product development.
- Open source high quality code and produce reproducible research.
Preferred Qualifications
- PhD in the field of Computer Science, Computer Engineering, Artificial Intelligence, or a relevant technical field, or equivalent practical experience.
- Proven track record of achieving significant results and publications as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as NeurIPS, ICML, ICLR, MLSys, or other similar venues.
- Demonstrated research and software engineering experience via work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
