Our vision is to transform how the world uses information to enrich life for all.
Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.
The Smart Manufacturing and AI team at Micron Technology is looking for GPU Performance Engineer. Our mission is to deliver industry-winning machine learning, custom GenAI, and Agentic AI solutions to power Micron’s dominance in the highly competitive memory solutions market. Qualified applicants will have experience in a variety of data and cloud technologies and have extensive practice modeling data, querying, and deploying scalable data pipelines to execute machine learning models and AI agents. You will collaborate with Data Scientists, Data Engineers, and expert users to build and deploy scalable AI/ML solutions that drive value and insight from Micron’s manufacturing processes and systems.
Responsibilities- Architect and complete large-scale custom model training and fine-tuning jobs (SFT, RLHF) on multi-node, multi-GPU clusters.
- Optimize training throughput and memory efficiency using distributed training strategies (FSDP, DeepSpeed, Megatron-LM) and mixed-precision techniques (FP16/BF16).
- Design and develop autonomous AI Agents capable of multi-step reasoning, planning, and tool execution to automate complex manufacturing workflows.
- Analyze and profile complex workloads (e.g., LLM training, Rendering pipelines) to identify bottlenecks in compute, memory bandwidth, and latency.
- Write and optimize high-performance kernels using CUDA, HIP, or custom assembly (PTX/SASS) to unlock hardware capabilities.
- Collaborate with Hardware Architects to define features for next-generation GPUs based on workload characterization.
- Design and implement performance regression testing suites to catch degradations in drivers or compilers.
- Mentor junior engineers on parallel programming paradigms and optimization techniques.
- Technical Degree required. Ph.D. in Computer Science or Statistics background highly desired.
- Deep understanding of GPU architecture (memory hierarchy, tensor cores, NVLink), GPU resource management (cloud & on‑prem), 5+ years in performance optimization/parallel computing/low‑level systems, and deep expertise in C++ with GPGPU frameworks (CUDA preferred; HIP/OpenCL/Metal acceptable).
- Hands-on experience with DDP, FSDP, model parallelism, and building end‑to‑end ML systems that automate training, testing, and deployment.
- Proficiency with LLMs including prompt engineering, function calling/tool use, CoT reasoning; fine‑tuning using PEFT techniques (LoRA, QLoRA); and optimizing inference engines (vLLM, TensorRT‑LLM).
- Experience developing GenAI applications and AI agents using frameworks such as LangChain, LangGraph, LlamaIndex, and AutoGen, with strong ML framework knowledge (PyTorch required; TensorFlow, scikit‑learn, etc.).
- Strong programming or scripting skills in Python (preferred) or Java. Experience with CI/CD and cloud-native tools such as Git, Jenkins, Docker, and Kubernetes is essential. Applicants should work on innovative cloud development, communicate well, and prioritize delivery in fast-paced settings.
- Experience with HPC job schedulers (e.g., Slurm) and orchestrating large‑scale GPU workloads on Kubernetes using tools like Ray and Kubeflow.
- Knowledge of CUDA programming, Triton kernels, and building custom C++ extensions for PyTorch to accelerate workloads.
- Experience designing and orchestrating collaboration between specialized agents in multi‑agent architectures.
- Deep knowledge of mathematics, probability, statistics, and algorithms.
- Demonstrated ability to evolve data science prototypes into production systems, with knowledge of computer vision and/or signal processing techniques for classification and feature extraction.
Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.
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