Software Engineer, Machine Learning

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

• Lead projects to research, design, develop, and test large-scale machine learning models and algorithms for Ads Ranking problems.
• Develop solutions for a wide range of ranking, classification, recommendation, and optimization problems, eg click-through or conversion rate prediction, click-fraud detection, ads ranking, text/sentiment classification, personalized recommendations by employing a variety of machine learning techniques including deep learning, natural language processing, collaborative filtering and clustering.
• Provide technical leadership for the team by creating roadmaps and setting long-term direction for developing industry-leading machine learning technology.
• Apply extensive knowledge of Ads business and systems and collaborate with other teams to identify impactful problems and architect highly scalable and efficient technical solutions using machine learning, large-scale data processing and distributed computing.
• Working on problems of diverse scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models.
• Demonstrates good judgment to 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.
• Develop deep insights through rigorous data analysis and leverage them for detecting and troubleshooting problems as well as identifying ways to enhance solutions.
• Receiving little instruction from supervisor, manage projects by setting goals, prioritization, preparing project plans, tracking progress, reporting updates, identifying and mitigating risks.
• Adapt standard machine learning methods to best exploit modern parallel environments (eg distributed clusters, multicore SMP, and GPU).

Minimum Qualifications

• Requires a Bachelor’s degree in Computer Science, Computer Software, Computer Engineering, Biotechnology, Applied Sciences, Mathematics, Physics, or related field, followed by seven years of progressive, post-baccalaureate work experience in the job offered or in a computer-related occupation.
  
  Requires seven years of experience in the following:
• 1. Leading Machine Learning projects including architecting solutions, creation of roadmaps and setting project goals
• 2. Researching, developing and deploying machine learning models and algorithms in at least one of the following areas: ranking and recommendation systems, pattern recognition, NLP, data mining or artificial intelligence
• 3. Building distributed computing applications using Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark
• 4. Working with large-scale distributed databases using Hive, Presto or Spark
• 5. Translating insights into business recommendations, product enhancements and new applications
• 6. Developing and debugging using C, C++ or Java
• 7. Scripting languages: Perl, Python, PHP, or shell scripts
• 8. Relational databases and SQL
• 9. Software development tools: Code editors (Vim or Emacs), and revision control systems (Subversion, Git, Mercurial or Perforce)
• 10. Linux, UNIX, or other *nix-like OS including commands related to navigation, file manipulation, search and system performance
• 11. Evaluating new functionality by designing experiments, performing A/B tests and making launch decisions
• 12. Designing and building highly-scalable performant solutions using distributed systems with established partition tolerance, consistency, and availability guarantees
• 13. 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.

LocationsAbout Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps 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. People who choose to build their careers by building with us at Meta help shape a future that will ta