At Facebook, we use machine learning across a diverse set of applications to help people discover better content more quickly, and to connect with the things that matter most to them. We strive to find ways to deliver more engaging content in News Feed, rank search results more accurately, and present the most relevant ads possible.
In order to meet the demands of our scale, we approach machine learning challenges from a system engineering standpoint, pushing the boundaries of scalable computing and tying together numerous complex platforms to build models that leverage trillions of actions. Our research and production implementations leverage many of the innovations being generated from Facebook's research in Distributed Computing, Artificial Intelligence and Databases, and run on the same hardware and network specifications that are being open sourced through the Open Compute project.
As a Software Engineer or Research Scientist at Facebook, you will help build the next generation of machine learning systems behind Facebook's products, create web applications that reach millions of people, build high volume servers and be a part of a team that's working to help connect people around the globe.
Suggest, collect and synthesize requirements and create effective feature roadmap
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
Must be available to start employment on or before December 31, 2019
Interpersonal experience: cross-group and cross-culture collaboration
Research and/or work experience in machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision
Experience in systems software or algorithms
Knowledge in Java or C++, Perl, PHP or Python
Problem solving experience
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
Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment