Principal Engineer, MLE, SMAI

Principal Engineer, MLE, SMAI

Micron Technology, Smart Manufacturing & AI team seeks a Machine Learning Engineer (Principal). The role involves leading ML, custom GenAI, and Agentic AI solutions across manufacturing processes and systems.

• 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, Deep Speed, 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 (e.g., Lang Chain, Lang Graph, 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 data management systems (Snowflake, Google Cloud platforms) to enable AI/ML and Agentic solutions.
• Build and maintain CI/CD pipelines of machine learning and AI Agent solutions in the cloud.

• 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 is preferred, but HIP, OpenCL, or Metal are 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 timely engineering, fine‑tuning (LoRA/QLoRA), inference optimization (vLLM, Tensor
  
  RT‑LLM), and development of GenAI applications/agents using Lang Chain, Llama Index, Auto Gen, and PyTorch.
• Proficient programming skills in Python (preferred) or Java, along with experience in CI/CD and cloud‑native tools such as Git, Jenkins, Docker, and Kubernetes. Candidates should have strong communication abilities and perform well in dynamic settings. A Bachelor’s or Master’s degree or equivalent experience in Computer Science, Statistics, or a related field is expected.

• A Ph.D. in Computer Science or Statistics, or comparable experience, is highly desired.
• 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 to accelerate workloads.
• Experience crafting and orchestrating collaboration between specialized agents in multi‑agent architectures.
• Deep knowledge of mathematics, probability, statistics, and algorithms. Proven track record to evolve data science prototypes into production systems, with knowledge of computer vision and/or signal processing techniques for classification and feature extraction.

Machine Learning Engineer 5 – Machine Learning Engineering MTS. Relocation Level: TBD.

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.