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AI Infrastructure Engineer Graduate (Algorithm Infrastructure) - 2027 Start (PhD)
San Jose, California · Full-time · Posted Oct 28, 2026
- Education
- Completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline; the posting also lists Computer Science, Software Engineering, Artificial Intelligence, Mathematics, or related fields.
About the job
Build and optimize large-scale inference infrastructure for language, vision-language, and multimodal AI systems.
What you'll do
- Develop distributed serving, scheduling, load balancing, and batch formation for large-scale online traffic.
- Optimize distributed inference for 200B+ and multimodal models to improve production throughput and latency.
- Develop high-performance kernels and explore AI-driven tools for kernel optimization, tuning, validation, deployment, and operations.
What they ask for
- Familiarity with large-model architectures and strong system design skills for complex, high-concurrency environments.
- Strong understanding of asynchronous scheduling, resource pooling, and load balancing in distributed microservice systems.
- Strong engineering skills in performance optimization and production system development.
Tools
CUDA, Triton
AI focus
Build inference infrastructure for large-scale language, vision-language, and multimodal AI; explore AI Agents for kernel optimization, performance tuning, consistency validation, deployment pipelines, and intelligent operations.
Model-written summary · the original posting is authoritative