Research Scientist, Machine Learning for Monetization (PhD)

$117,000 - $173,000/Yr

Meta - Sunnyvale, CA

Full-time - Entry Level

Sunnyvale, CA

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About the position

The Research Scientist, Machine Learning for Monetization role at Meta focuses on developing advanced machine learning technologies to enhance monetization strategies for businesses. This position involves creating scalable classifiers and tools, adapting machine learning methods for modern environments, and contributing to innovative research that drives product development. The role is integral to shaping the future of communication and financial tools for businesses in the digital economy.

Responsibilities

• Develop highly scalable classifiers and tools leveraging Machine Learning, data regression, and rules based models.
• Suggest, collect, and synthesize requirements to create an effective feature roadmap.
• Adapt standard Machine Learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
• Lead and contribute to cutting-edge research that results in industry-leading tech demos and/or publications.
• Collaborate closely with cross-functional partners and contribute towards Meta's research product development.

Requirements

• 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.
• Currently has, or is in the process of obtaining, a PhD degree in Machine Learning, Artificial Intelligence, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Hands-on experience in Deep Learning algorithms and techniques, e.g., convolutional neural networks (CNN), transformers, quantization, data efficient learning, or similar.
• Experience with Python, C++, or Java, and scripting languages such as Perl, Python, PHP, shell scripts, or similar.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

Nice-to-haves

• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, or similar.
• Experience working and communicating cross-functionally in a team environment.
• Experience on Data Efficient Learning, domain adaptation, Semi-supervised Learning, etc.
• Exposure to architectural patterns of large scale software applications.
• Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Paid time off
• Flexible scheduling
• Professional development opportunities
• Employee stock purchase plan
• Tuition reimbursement
• Wellness programs