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Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.
Job Responsibility:
Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems
Have industry experience working on a range of ranking, classification, recommendation, and optimization problems, e.g. payment fraud, click-through or conversion rate prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection
Working on problems of moderate scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models
Suggest, collect, analyze and synthesize requirements and bottleneck in technology, systems, and tools
Develop solutions that iterate orders of magnitude with a higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the-art deep learning techniques
Receiving general instruction from supervisor, 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)
Requirements:
Requires a Master’s degree (or foreign equivalent) in Computer Science, Computer Software, Intelligent Information Systems, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field
Requires completion of a university-level course, research project, internship, or thesis in the following: Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
Translating insights into business recommendations
Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark
Developing and debugging in C, C++, and Java
Scripting languages: Perl, Python, PHP, or shell scripts
C, C++, C#, or Java
Python, PHP, or Haskell
Relational databases and SQL
Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
Linux, UNIX, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting
Build highly-scalable performant solutions
Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction
Applying algorithms and core computer science concepts to real world systems as evidenced by recognizing and matching patterns from different areas of computer science in production systems