Research Engineer

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.

Qualifications: Requires a Master's degree (or foreign degree equivalent) in Computer Science, Data Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field Requires completion of a university-level course, research project, internship, or thesis in the following: 1. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow 2. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems 3. Translating insights into business recommendations 4. Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark 5. Developing and debugging in C, C++, and Java 6. Scripting languages: Perl, Python, PHP, or shell scripts 7. C, C++, C#, or Java 8. Python, PHP, or Haskell 9. Relational databases and SQL 10. Build highly-scalable performant solutions 11. Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction 12. 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 13. Distributed systems

Responsibilities: Research, design, develop, and test systems-level software, compilers, and network distribution software for massive prediction problems. Drive cutting edge research and development for machine learning platform. Create new AI models, tools and infrastructure that unlock the capabilities of Meta technology. Productionize research results, and work with scientists, software engineers, hardware engineers and designers to advance the company's AI or AR/VR agenda. Address common challenges, long term needs across the science teams, and lead unification of common workstreams under uniform frameworks. 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 bottlenecks 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). Design methods, tools, and infrastructure to analyze and leverage rich multimodal data sets. Build tools to transition and deliver ML models from research into production. Investigate and apply model reduction techniques (e.g., pruning, distillation, and quantization) to shorten research and the ML model to production timelines.