Senior Edge AI Inference Optimization Engineer

PVH (Tommy Hilfiger/Calvin Klein); Santa Clara (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Intel Benefits

Job summary

Intel is seeking a seasoned software engineer to accelerate AI inference on edge hardware. You will optimize llama.cpp/vLLM, tune KV cache, batching and scheduling, and push quantization strategies to balance speed and quality.

This role focuses on low-latency, privacy-preserving AI workloads run on client devices. You will work across hardware tiers, benchmark performance, and contribute upstream fixes to open-source engines, helping deliver safe, efficient AI at scale while maintaining energy

Qualifications

• BS/MS in CS/EE/Math or related STEM field.
• 8+ years software development background.
• Strong in C++ and/or Python; reading systems-level code.
• Experience with LLM inference and KV cache.

Responsibilities

• Profile and optimize local inference for latency and throughput on edge hardware.
• Tune KV cache, batching, and scheduling for interactive workloads.
• Drive quantization strategy and validate quality impact.
• Cut CPU overhead and improve engine startup, model load, and lifecycle.
• Benchmark across hardware tiers and publish honest performance comparisons.
• Upstream fixes and patches to open-source engines where it helps us

Skills

C++

Python

LLM inference

Linux

Profiling

Optimization

Education

BS/MS in CS/EE/Math or related STEM field

Tools

llama.cpp

vLLM

ggml

CUDA

Job description

Intel is seeking a seasoned software engineer to accelerate AI inference on edge hardware. You will optimize llama.cpp/vLLM, tune KV cache, batching and scheduling, and push quantization strategies to balance speed and quality.

This role focuses on low-latency, privacy-preserving AI workloads run on client devices. You will work across hardware tiers, benchmark performance, and contribute upstream fixes to open-source engines, helping deliver safe, efficient AI at scale while maintaining energy