About the job
Apply relevant AI infrastructure and hardware acceleration techniques to build & optimize our intelligent ML systems that improve Meta’s products and experiences.
Responsibilities
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
Minimum
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
Preferred
No preferred qualifications listed.