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Research Engineer, Fundamental AI Research - CoreML and Optimization
MetaNew York City, United Statesfull_timeVerifiedPosted 19 Feb 2025
💰 $173,000/yr($112,500/yr – $173,000/yr)
About the role
Meta is seeking a Research Engineer to join the Fundamental AI Research (FAIR) team, a research organization committed to advancing the field of artificial intelligence. We are seeking individuals who are passionate in solving engineering challenges in developing new algorithms and software to accelerate our progress towards advanced machine intelligence. Candidates will have an opportunity to make fundamental contributions on improving both the training and inference efficiency of deep learning models and apply their ideas at an unprecedented scale. Some aspects of this role require optimization algorithms design, implementation and deployment, especially on large-scale distributed infrastructure.Research Engineer, Fundamental AI Research - CoreML and Optimization Responsibilities
$56.25/hour to $173,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about
- Carry out cutting-edge research to advance the field of machine learning and artificial intelligence.
- Perform research that enables learning the semantics of data (images, video, text, audio, and other modalities).
- Devise rigorous engineering and data-driven approaches for efficient training of AI models and algorithms implementation.
- Contribute research that leads to innovations in: optimization algorithms, distributed computing, and novel AI model architecture.
- 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.
- 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.
- 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 convolutional nets and Transformers.
- Experience in solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view 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.
- 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).
$56.25/hour to $173,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about
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