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. To apply, click "Apply to Job" online on this web page.

Software Engineer (Machine Learning) Responsibilities

• Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems.


• Have industryexperience working on a range of ranking, classification, recommendation, and optimization problems ,problems, e.g. payment fraud, click-through or conversion rate prediction, click-frauddetection, 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-theart 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).

Minimum Qualifications

• Master's degree in Computer Science, Engineering, Mathematics, or a related field. 24 months of experience in the job offered or in a related occupation. Experience must include 24 months involving the following:


• 1. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems


• 2. Python, PHP, or Haskell


• 3. Relational databases and SQL


• 4. Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)


• 5. Conducting design and code reviews


• 6. Object-oriented software development


• 7. Building maintainable and testable codes bases including API design and unit testing techniques


• 8. Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)


• 9. 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


• 10. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems.

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