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About the Role
Lead a team at the intersection of AI, distributed systems, and hardware architecture. This role drives ML model efficiency and scalability, infrastructure costs, and enables embedded AI capabilities, directly supporting Meta's ability to train and serve AI models for wearable products.
Responsibilities
- Build and retain an engineering team, providing coaching, mentorship, and performance management.
- Engage in design reviews, architecture decisions, and technical trade-offs, defining technical vision with Tech Leads.
- Drive complex hardware-software co-design projects to completion, managing roadmaps, timelines, and risk mitigation.
- Collaborate with AI Infra, Hardware Engineering, Product, and Research, representing the team to leadership.
Requirements
- 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 deeply 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.
Skills
- AI/ML systems
- Distributed/HPC systems
- Software tooling and infrastructure
- Model optimization with GPUs/accelerators
- PyTorch
- TensorFlow
- AI compilers
- High-performance kernel development
- Hardware enablement
- Prompt/context engineering
- Agent orchestration
- Performance optimization/profiling
- Responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience Level
- 3+ years managing software engineering teams
Education Level
- M.S. or Ph.D. in CS, EE, or related field
Salary/Compensations
- $184,000/year to $257,000/year
Benefits
- bonus
- equity
- benefits