The role focuses on optimizing inference engines for local and edge environments at Intel. The team aims to enhance AI performance while ensuring data privacy and cost-effectiveness. Candidates will work on profiling and optimizing models for latency, throughput, and memory on various hardware. This position requires a blend of software development expertise and a deep understanding of AI inference technologies.

• BS/MS in Computer Science, Electrical Engineering, Mathematics, or a related STEM field
• 8+ years of software development experience
• Strong proficiency in C++ and/or Python with the ability to read systems-level code
• Experience with LLM inference, including attention, KV cache, and decoding
• Expertise in profiling and optimizing performance issues on CPU or GPU
• Familiarity with Linux, build systems, and low-level debugging

• Profile and optimize local inference for latency, throughput, and memory on edge hardware
• Tune KV cache, continuous batching, and scheduling for interactive agent workloads
• Drive quantization strategy and validate quality impact with the Post-Training team
• Reduce CPU overhead and improve engine startup, model load, and lifecycle management
• Benchmark performance across hardware tiers and publish performance comparisons
• Contribute upstream fixes and patches to open-source engines where beneficial

• Intel offers a comprehensive benefits package including competitive pay, stock programs, healthcare coverage, retirement plans, paid time off, parental leave, and programs supporting employee wellbeing and professional development.