Meta
AI Software Engineer, Systems ML - Wearables AI
$154K–$217K
Seattle, WA · Full-time · Posted Aug 13, 2026
- Experience
- Bachelor’s: 7+ years; master’s: 4+ years; PhD: 3+ years in AI framework development or accelerating deep-learning models on hardware architectures.
- Education
- Bachelor’s, master’s, or PhD in Computer Science, Computer Engineering, or a relevant technical field; the posting also accepts equivalent practical experience for the general degree qualification.
About the job
Build and optimize AI infrastructure and intelligent machine-learning systems for Meta’s platforms, with a focus on systems challenges, hardware acceleration, and cross-team impact.
What you'll do
- Apply AI infrastructure and hardware acceleration techniques to build and optimize ML systems; set goals for project impact, system design, and developer efficiency.
- Define use cases and develop methodologies and benchmarks to evaluate approaches; use data-driven analysis to deliver results across teams.
- Apply ML infrastructure expertise, mentor engineers and research scientists, and improve engineering quality.
What they ask for
- Specialized experience in one or more areas such as hardware or GPU architecture, ML compilers or systems, AI infrastructure, high-performance computing, performance optimization, ML frameworks, numerics, or software/hardware co-design.
- Experience developing AI-system infrastructure or AI algorithms in C/C++ or Python, and technical leadership experience.
- Experience implementing responsible, ethical AI practices.
- Bachelor’s degree plus 7+ years, master’s degree plus 4+ years, or PhD plus 3+ years of experience in AI framework development or accelerating deep-learning models on hardware architectures.
Nice to have
- Experience with recommendation and ranking models, distributed systems, or on-device algorithm development.
- Demonstrated ability to use AI tools to redesign workflows and achieve measurable impact; ongoing AI skill development.
Pay
$154,003/year to $217,000/year (base salary); bonus + equity (amount not stated)
Tools
C/C++, Python, PyTorch
AI focus
Develop and accelerate ML systems and AI infrastructure, including hardware acceleration, responsible AI practices, recommendation and ranking models, and AI-assisted workflow improvements.
Model-written summary · the original posting is authoritative