Engineering Manager, AI Infra & ML Systems

Meta; Burlingame (CA); On-site; USD 184,000 - 257,000; Full time

Job summary

Meta is seeking a Software Engineering Manager to lead a neural interface ML infra team in a role that blends AI/ML, distributed systems, and hardware architecture. You will drive model efficiency, scalability, and cost optimization while enabling embedded AI for wearable products.

Responsibilities include building and mentoring the team, making architectural trade-offs, and aligning with AI Infra, Hardware, Product, and Research leaders to deliver impactful outcomes.

Qualifications

• 3+ years managing software engineering teams with a track record of delivering measurable outcomes
• Technical background in at least two of: AI/ML systems, distributed/HPC systems, software tooling and infrastructure or model optimization with GPUs/accelerators
• Demonstrated ability to engage deep in technical work and guide decisions
• Proven track record growing engineers
• Experience communicating technical strategy and influencing cross-functional stakeholders through written proposals and presentations

Responsibilities

• People Leadership: Build/retain an engineering team
• provide coaching, mentorship, and performance management
• Technical Leadership: Engage in design reviews, architecture decisions, and technical trade-offs
• define technical vision with Tech Leads
• Execution: Drive complex hardware-software co-design projects to completion
• manage roadmaps, timelines, and risk mitigation
• Cross-Functional Partnership: Collaborate with AI Infra, Hardware Engineering, Product, and Research
• represent the team to leadership

Skills

People leadership

Technical leadership

Cross-functional collaboration

Communication

AI/ML systems

GPU/accelerators

Education

MS/PhD in CS, EE, or related field

Tools

PyTorch

TensorFlow

AI frameworks

Job description

Meta is seeking a Software Engineering Manager to lead a neural interface ML infra team in a role that blends AI/ML, distributed systems, and hardware architecture. You will drive model efficiency, scalability, and cost optimization while enabling embedded AI for wearable products.

Responsibilities include building and mentoring the team, making architectural trade-offs, and aligning with AI Infra, Hardware, Product, and Research leaders to deliver impactful outcomes.