Principal Engineer, MLE, SMAI

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. 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). Build and develop autonomous AI agents capable of multi‑step reasoning, planning, and tool execution to automate complex manufacturing workflows. Implement agentic frameworks (LangChain, LangGraph, CrewAI) to orchestrate LLM interactions with internal APIs, databases, and software tools. Profile and debug GPU performance bottlenecks using tools like Nsight Systems or PyTorch Profiler to improve hardware utilization. Develop and sustain data/solution pipelines that support machine learning models and GenAI applications; build and optimize data structures in Snowflake and Google Cloud platforms; build and maintain CI/CD pipelines of machine learning and AI agent solutions in the cloud. Minimum Qualifications 10+ years of experience with deep expertise in GPU architecture (memory hierarchy, tensor cores, NVLink) and GPU resource management across cloud and on‑prem environments. 5+ years in performance optimization, parallel computing, and low‑level systems. Strong C++ skills and experience with GPGPU frameworks; CUDA preferred, HIP, OpenCL, or Metal acceptable. Hands‑on experience building end‑to‑end ML systems, including distributed training techniques (DDP, FSDP, model parallelism) and automated pipelines for training, testing, and deployment. Strong proficiency in LLMs, including fine‑tuning (LoRA/QLoRA), inference optimization (vLLM, TensorRT‑LLM), and development of GenAI applications/agents using LangChain, LlamaIndex, AutoGen, and PyTorch. Proficient programming skills in Python (preferred) or Java; experience with CI/CD and cloud‑native tools such as Git, Jenkins, Docker, and Kubernetes. Candidate should have strong communication abilities and perform well in dynamic settings. Bachelor’s or Master’s degree or equivalent experience in Computer Science, Statistics, or related field. Preferred Qualifications A Ph.D. in Computer Science or Statistics, or comparable experience. Experience with HPC job schedulers (e.g., Slurm) and managing 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. Experience crafting and orchestrating collaboration between specialized agents in multi‑agent architectures. Deep knowledge of mathematics, probability, statistics, and algorithms. Proven track record of evolving data science prototypes into production systems, with knowledge of computer vision and/or signal processing techniques for classification and feature extraction. Benefits Medical, dental, and vision plans that can be customized to meet individual and family needs. Income protection programs for illness or injury and paid family leave. Robust paid time‑off program and paid holidays. Micron is proud to be an equal opportunity workplace and 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. #J-18808-Ljbffr 1000 Micron Technology, Inc.