AI Infrastructure & Experience Engineer

Recent experience in model optimization requiredHardware & Compute:Proven experience with NVIDIA eco-systems and ARM64 architecture.Systems Programming:Advanced proficiency in C++, Python, and Rust. Deep familiarity with CUDA and the ability to author/debug custom CUDA kernels for compute-intensive tasks.AI/ML Frameworks:Extensive experience with modern inference engines (llama.cpp, TensorRT-LLM, Ollama) and orchestration frameworks (LiteLLM).Software Engineering:Robust understanding of asynchro

Job Category: Technical Job Title: AI Infrastructure & Experience Engineer Duties: Key Responsibilities Inference Optimization: Deploy and tune multiple LLMs and generative multimodal models on local inference hardware. Optimize performance metrics (TTFT, tokens/sec) via model quantization, caching strategies, and architecture-specific adjustments. Systems Engineering & CUDA: Leverage deep knowledge of the CUDA environment to build custom kernels, ensuring maximum utilization of the l

AI Inference Engineer Location:San Jose, CA Contract / C2H Duration: 6-12Months About the Role We are seeking a highly skilled AI Inference Engineer to join our team and drive the performance, scalability, and reliability of our large-scale model serving infrastructure. This role sits at the intersection of systems engineering, GPU optimization, and distributed infrastructure, and is ideal for someone who thrives on squeezing maximum performance out of production AI workloads. The ideal candida

Business Unit What the Role Entails 1.Architecture Research: Conduct in-depth research into the underlying hardware logic of various AI accelerators; evaluate the power-efficiency ratio and suitability of different heterogeneous architectures in the context of Large Language Model (LLM) inference and training. 2.Operator & Performance Optimization: Design and optimize high-performance operator libraries for large-scale cloud computing environments; resolve long-tail latency issues in hardware