Research Scientist, Machine Learning (PhD)

$117,000 - $173,000/Yr

Meta - San Francisco, CA

Full-time - Entry Level

San Francisco, CA

5,001-10,000 employees

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About the position

As a Research Scientist in Machine Learning at Meta, you will play a pivotal role in advancing the company's machine learning capabilities. This position involves tackling complex projects that leverage scalable computing to enhance how people connect globally. You will be responsible for the entire machine learning life-cycle, collaborating with top engineers and researchers to address significant social data and prediction challenges.

Responsibilities

• Develop highly scalable classifiers and tools leveraging machine learning, regression, and rules-based models
• Suggest, collect and synthesize requirements and create effective feature roadmap
• Build strong cross-functional partnerships and code deliverables in tandem with the engineering team
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
• Perform specific responsibilities which vary by team

Requirements

• Currently has, or is in the process of obtaining, a PhD degree or completing a postdoctoral assignment in the field of Computer Science, Computer Vision, Machine Learning or relevant technical field
• Experience programming in a relevant programming language
• Research and/or hands-on experience in one or more of the following areas: machine learning, NLP, recommendation systems, pattern recognition, data mining or artificial intelligence
• Relevant experience using frameworks such as PyTorch, TensorFlow or equivalent
• Proven experience to translate insights into business recommendations
• Experience with scripting languages such as Python, Javascript or Hack
• Experience building and shipping high quality work and achieving high reliability
• Experience in systems software or algorithms

Nice-to-haves

• Demonstrated software engineer experience via an internship, work experience, coding competitions, or contributions in open source repositories (e.g. GitHub)
• Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward
• Interpersonal experience working and communicating cross-functionally in a team environment
• Exposure to architectural patterns of large scale software applications
• PhD degree or research focused Master degree in ML areas

Benefits

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