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.
Responsibilities
Apply relevant AI infrastructure and hardware acceleration techniques to build & optimize our intelligent ML systems that improve Meta’s products and experiences. Goal setting related to project impact, AI system design, and infrastructure/developer efficiency. Directly or influencing partners to deliver impact through deep, thorough data-driven analysis. Drive large efforts across multiple teams. Define use cases and develop methodology & benchmarks to evaluate different approaches. Apply in depth knowledge of how the ML infra interacts with the other systems around it. Mentor other engineers / research scientists & improve the quality of engineering work in the broader team.
Qualifications
Bachelor's degree (or foreign degree equivalent) in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience and 1 year of work experience in the job offered or related occupation. Requires 1 year of experience in the following skills: Experience in AI infrastructure, high performance computing, performance optimizations, or Machine learning frameworks (e.g. PyTorch), numerics or SW/HW co-design AI-System infrastructure or AI algorithms in C/C++ or Python C, C++, Java, C#, Hack or other relevant coding languages Building large-scale infrastructure applications or similar experience in a corporate or start-up environment Designing and completing medium to large features independently without guidance Experience owning a particular component, feature or system 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 including file manipulation and simple commands 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 Leading major initiatives Leading projects and teams and Building and shipping high quality work