Software Engineer

Meta•Menlo Park, CA

About The Position

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.

Requirements

Requires a Master’s degree (or foreign equivalent) in Computer 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:
Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems
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
Distributed systems

Responsibilities

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).
Write design proposal to improve scaling of machine learning models in PyTorch and then implement them as code.
Work with partners in other orgs in Meta and open source to fix operational issues arising from using PyTorch code.