AI Hardware Engineering Intern (AI)

Location: Hybrid work model with on-site and off-site work; primary location in Santa Clara, California, United States, and additional location in Folsom, California, United States.

Salary: Annual target compensation of $100,598–$100,602 USD for US locations.

Company

hirify.global develops computing hardware, software, and AI infrastructure technologies.

What you will do

• Conduct technical research on CPUs, GPUs, AI accelerators, ASICs, memory systems, networking, storage, rack-scale architecture, power delivery, cooling, and cluster management.
• Analyze GenAI and agentic AI workloads, including transformer inference, mixture-of-experts models, multimodal models, real-time inference, and distributed serving.
• Evaluate prefill and decode pipelines, memory capacity and bandwidth, KV-cache management, compute utilization, interconnect bandwidth, latency, throughput, power, and total cost of ownership.
• Identify product and system gaps across hardware, developer tooling, performance libraries, deployment models, observability, and ecosystem enablement.
• Develop benchmarks, technical models, simulations, prototypes, and analysis tools; investigate bottlenecks across compute, memory, networking, storage, and software orchestration.
• Work with hirify.global technical teams, external ISVs, model providers, inference-engine developers, cloud providers, framework teams, and other ecosystem partners; present findings through diagrams, reports, recommendations, and executive-ready presentations.

Requirements

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, AI/ML, Systems Engineering, or a related technical discipline.
• Strong foundation in computer architecture, operating systems, distributed systems, parallel computing, AI/ML systems, high-performance computing, or systems software.
• Familiarity with generative AI models and inference concepts, including transformers, attention, token generation, model serving, quantization, batching, KV cache, long-context workloads, and latency-throughput trade-offs.
• Programming experience in one or more of C, C++, Rust, CUDA, SYCL, OpenCL, or a comparable low-level or performance-oriented language.
• Cumulative GPA of 3.0 or higher.
• Good understanding of firmware codebases, compilers, kernels, serving stacks, model architectures, and modern AI software layers such as PyTorch, Hugging Face Transformers, vLLM, SGLang, TensorRT-LLM, Triton, Kubernetes, and Neocloud design efficiencies.
• Experience supporting silicon hardware programs across multiple lifecycle phases and understanding of ASIC and SoC design, memory subsystems, interconnects, power management, cooling, observability, telemetry, and their impact on GenAI and LLM performance, cost, and execution KPIs.

Nice to have

• Coursework, research, or project experience in computer architecture, VLSI, digital design, ASIC/FPGA systems, compilers, kernel development, GPU programming, distributed systems, high-performance computing, or AI systems.
• Experience with profiling, tracing, or benchmarking CPU, GPU, accelerator, network, memory, storage, or software performance.
• Familiarity with hirify.global Xeon processors, hirify.global GPUs, NVIDIA GPUs, AMD GPUs, TPUs, custom AI accelerators, FPGAs, or inference ASICs.
• Understanding of cache behavior, DRAM, HBM, memory bandwidth and capacity, latency, data locality, DMA, and data movement.
• Experience with vLLM, SGLang, Hugging Face Transformers, PyTorch, Triton, or Ray.
• Familiarity with Linux, containers, Kubernetes, distributed storage, RDMA over Ethernet, InfiniBand, CXL, PCIe, NVMe, UALink/eSUN interconnects, silicon photonics, and cluster-management software.
• Experience with simulation, modeling, emulation, RTL, FPGA prototyping, firmware, driver development, or low-level debugging.
• Experience contributing to open-source systems, ML infrastructure, compiler, kernel, framework, or performance-engineering projects.

Culture & Benefits

• Hybrid work model combining on-site work at an assigned hirify.global site with off-site work.
• Health, retirement, and vacation benefits.
• Competitive pay and stock bonuses.
• Work within a highly technical team of researchers and engineers addressing AI hardware and infrastructure challenges.