Lead AI Systems Engineer - Production ML & Platforms

Meta; Menlo Park (CA); On-site; USD 219,000 - 301,000; Full time

Job summary

Meta seeks a distinguished Software Engineer with deep AI focus to shape large-scale AI systems across Meta’s apps. You will lead architectural direction for training, inference, ranking and deployment pipelines, driving standards and long-term platform strategy.

You will mentor engineers, collaborate with research and product teams, and advance responsible AI practices while delivering measurable improvements to product metrics at global scale.

Qualifications

• Bachelor's degree is required or equivalent practical experience.
• 12+ years of software engineering experience with AI in production.
• Experience delivering large-scale AI or ML systems at significant scale (training, serving, ranking, foundation models).
• Experience leading multi-team technical initiatives end-to-end with measurable outcomes.
• Ability to communicate complex AI designs to both technical and non-technical audiences.

Responsibilities

• Identify and solve complex AI systems engineering challenges at global scale.
• Define extensible foundations and standards for AI model development and deployment pipelines.
• Drive the technical vision and multi-year roadmap for AI platform capabilities across teams.
• Evaluate emerging AI architectures and translate findings into actionable strategy.
• Lead design and implementation of AI systems with rigorous testing and reliability.

Skills

AI Systems Engineering

Technical Leadership

Cross-functional Collaboration

Strategic Planning

Mentoring

Communication

Systems Architecture

Education

Bachelor's degree in Computer Science / Computer Engineering or equivalent

Job description

Meta seeks a distinguished Software Engineer with deep AI focus to shape large-scale AI systems across Meta’s apps. You will lead architectural direction for training, inference, ranking and deployment pipelines, driving standards and long-term platform strategy.

You will mentor engineers, collaborate with research and product teams, and advance responsible AI practices while delivering measurable improvements to product metrics at global scale.