Software Engineer, Systems

Responsibilities

• Apply relevant AI infrastructure and hardware acceleration techniques to build and optimize intelligent ML systems that improve Meta’s products and experiences.
• Set goals related to project impact, AI system design, and infrastructure/developer efficiency.
• Directly or influence partners to deliver impact through data-driven analysis.
• Drive large initiatives across multiple teams.
• Define use cases and develop methodologies and benchmarks to evaluate different approaches.
• Apply in-depth knowledge of how the ML infrastructure interacts with surrounding systems.
• Mentor other engineers and research scientists to improve the quality of engineering work in the broader team.

Qualifications

• Bachelor's degree (or foreign degree equivalent) in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience, plus 1 year of work experience in the offered role or related occupation.
• 1 year of experience in AI infrastructure, high-performance computing, performance optimizations, or machine learning frameworks (e.g., PyTorch), numerics, or SW/HW co-design.
• Experience with AI-system infrastructure or AI algorithms in languages such as C/C++, Python, Java, C#, Hack, or other relevant coding languages.
• Experience building large-scale infrastructure applications or similar experience in a corporate or start-up environment.
• Ability to design and complete medium to large features independently without guidance.
• Experience owning a particular component, feature, or system.
• Knowledge of relational databases and SQL.
• Familiarity with software development tools (code editors such as Vim or Emacs) and revision control systems (Subversion, Git, or Perforce).
• Experience with Linux/UNIX or other *nix-like operating systems, including file manipulation and basic commands.
• Knowledge in data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction.
• Ability to apply algorithms and core computer science concepts to real-world systems in production environments.
• Experience leading major initiatives and teams, and delivering high-quality work.