Research Engineer (AI)
(Menlo Park, CA – New York, NY – Paris, France)
Facebook’s mission is to give people the power to share, and make the world more open and connected. Through our growing family of apps and services, we’re building a different kind of company that helps billions of people around the world connect and share what matters most to them. Whether we’re creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to make the world more open and accessible. Connecting the world takes every one of us—and we’re just getting started.
We are looking for research engineers with expertise in machine learning, artificial intelligence, and software engineering. In this role, you will embed deeply with researchers at Facebook AI Research (FAIR) and develop experiments and prototypes at the frontier of AI Research. You will need to engage with research topics and cover new domains quickly; build deep expertise with Facebook data and tools; apply high standards to the research code around you and develop an ability to identify highly impactful projects in a complex and unexplored domain. You will gain valuable experience in artificial intelligence and AI, publish academic papers and help push forward the understanding of learning and intelligent systems.
- Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies
- Combine broad and deep knowledge of relevant research domains with the ability to synthesize a wide range of requirements to make significant contributions to the feature roadmap for the applied machine learning platform
- Apply expert coding skills to platform development projects in partnership with other engineers on ranking and infrastructure teams
- Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
- BS degree in Computer Science or related quantitative field
- Experience in machine learning and optimization
- Experience building systems based on machine learning and/or deep learning methods
- Experience in developing and debugging in C/C++, Java, and/or Scala
- Experience with filesystems, server architectures, and distributed systems
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