NEXadept Hiring! Full Time LLM Inference Performance Engineer in - Ricebowl

About the Role

We are looking for an LLM Inference Performance Engineer to optimize large-scale LLM inference performance across TPU/GPU and other AI accelerators.

You will work across LLM inference, kernels, compilers, and runtime systems, improving latency, throughput, scalability, and overall inference efficiency.

Responsibilities

• Optimize LLM inference performance on TPU/GPU and other AI accelerators
• Develop and optimize inference backends, kernels, and runtime components
• Optimize Attention, GEMM, KV Cache, Sampling, fused kernels and other performance-critical workloads
• Work with technologies such as JAX, XLA, Pallas, CUDA, Triton or related frameworks
• Build benchmarking and profiling tools to identify performance bottlenecks
• Collaborate with model, inference, compiler, and hardware teams to improve production performance

Requirements

• Bachelor’s degree or equivalent experience in CS, Engineering, ML, Systems, or related fields
• Experience in LLM inference, ML systems, hardware acceleration, or performance optimization
• Strong programming skills in C++ and/or Python
• Understanding of GPU/TPU architecture, memory behavior, kernels, or ML workload performance
• Experience with performance profiling and benchmarking