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Responsibilities
- Apply relevant AI infrastructure and hardware acceleration techniques to build & optimize our intelligent ML systems that improve Meta’s products and experiences
- Goal setting related to project impact, AI system design, and infrastructure/developer efficiency
- Directly or influencing partners to deliver impact through 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
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Specialized experience in one or more of the following machine learning/deep learning domains: Hardware accelerators architecture, GPU architecture, machine learning compilers, or ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine learning frameworks (e.g. PyTorch), numerics and SW/HW co-design
- Experience developing AI-System infrastructure or AI algorithms in C/C++ or Python
Preferred Qualifications
- Technical leadership experience
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Experience with recommendation and ranking models
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience with distributed systems or on-device algorithm development
- A Bachelor's degree in Computer Science, Computer Engineering, relevant technical field and 7+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a Master's degree in Computer Science, Computer Engineering, relevant technical field and 4+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a PhD in Computer Science, Computer Engineering, or relevant technical field and 3+ years of experience in AI framework development or accelerating deep learning models on hardware architectures
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
$154,003/year to $217,000/year + bonus + equity + benefits
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