Micron Technology
Semiconductor
PrincipalMachineLearningEngineer
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“Principal Machine Learning Engineer at Micron Technology. Skills: Machine Learning, GenAI, Agentic AI, GPU architecture. Architect custom model training jobs. Complete custom model training jobs”
What You'll Achieve.
Generate value from manufacturing processes; Generate insight from manufacturing processes; Generate value from manufacturing systems; Generate insight from manufacturing systems
Industry & Context.
Debugging GPU performance bottlenecks
What They're Looking For.
Must Have
10+ years GPU architecture experience, 5+ years performance optimization, 5+ years parallel computing, 5+ years low-level systems, C++ skills, GPGPU frameworks experience, End-to-end ML systems experience, Distributed training techniques experience, Automated pipelines experience, LLMs proficiency, Fine-tuning proficiency, Inference optimization proficiency, GenAI applications/agents development, Python programming skills, CI/CD experience, Cloud-native tools experience, Bachelor's degree or equivalent experience
Nice to Have
Ph.D. in Computer Science or Statistics, HPC job schedulers experience, Manage large scale GPU workloads experience, CUDA programming knowledge, Triton kernels knowledge, Build custom C++ extensions knowledge, Craft and orchestrate teamwork between niche agents, Deep knowledge of mathematics, Deep knowledge of probability, Deep knowledge of statistics, Deep knowledge of algorithms, Evolve data science prototypes into production systems, Computer vision techniques knowledge, Signal processing techniques knowledge
What You'll Do.
Architect custom model training jobs
Complete custom model training jobs
Architect fine-tuning jobs
Complete fine-tuning jobs
Optimize training throughput
Optimize memory efficiency
Automate manufacturing workflows
Implement Agentic frameworks
Orchestrate LLM interactions
Profile GPU performance bottlenecks
Debug GPU performance bottlenecks
Improve hardware utilization
Develop data pipelines
Sustain data pipelines
Develop solution pipelines
Sustain solution pipelines
Build data structures
Optimize data structures
Enable AI/ML solutions
Enable Agentic solutions
Build CI/CD pipelines
Maintain CI/CD pipelines
How You'll Work.
Team & Collaboration
Work with Data Scientists; Work with Data Engineers; Work with expert users
Communication Scope
Communication abilities
Process & Methodology
CI/CD pipelines
Full Job Description
**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 an ambitious Machine Learning Engineer. Our mission is to provide leading machine learning, custom GenAI, and Agentic AI solutions that support Micron’s leadership in the competitive memory solutions market. Qualified applicants will have experience with various data and cloud technologies and strong skills in modeling data, querying, and deploying scalable data pipelines to complete machine learning models and AI agents. You will work closely with Data Scientists, Data Engineers, and expert users to build and launch scalable AI/ML solutions that generate 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). * 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., 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 data management systems (Snowflake, and Google Cloud platforms) to enable AI/ML and Agentic so
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