Micron Technology
Semiconductor
StaffMachineLearningEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Staff Machine Learning Engineer at Micron Technology. Skills: Machine Learning, Data Engineering, Generative AI, MLOps. Analyze large datasets. Uncover patterns, trends, and insights”
What You'll Achieve.
Drive value from manufacturing processes; Drive insight from manufacturing processes; Enhance product capabilities; Balance performance with cost efficiency; Enable continuous improvement
Industry & Context.
Solve complex problems
What They're Looking For.
Must Have
3+ years building end-to-end ML systems, Automating model training, testing, and deployment, Experience with ML frameworks, Proficient in Python or Java, Experience developing APIs, Experience with event-driven pipelines, Skilled in scalable data engineering, SQL proficiency, Data architecture design, Hands-on experience with cloud and DevOps tools, Analytical skills, Communication skills, Collaboration skills
Nice to Have
Foundation in machine learning and deep learning, Solid grounding in probability and statistics, Ability to productionize data science prototypes, Hands-on experience building Generative AI solutions, Experience with intelligent agents, Expertise in semantic search, Experience with RAG, Experience with GraphRAG, Experience with NLP, Experience with prompt engineering, Experience with LLM fine-tuning/evaluation, Experience with end-to-end data and engineering workflows, Experience with big data processing, Experience with CI/CD tools
What You'll Do.
Analyze large datasets
Integrate emerging techniques
Maintain data pipelines
Support model training
Support model deployment
Collaborate on data preprocessing
Collaborate on feature engineering
Improve input data quality
Improve model performance
Design data architectures
Optimize data architectures
Develop custom applications
Implement CI/CD pipelines
Deploy models in production
Evaluate models in production
Monitor models in production
Partner with Product teams
Partner with Engineering teams
Define Generative AI integration strategies
Execute Generative AI integration roadmaps
Translate analytics into recommendations
How You'll Work.
Team & Collaboration
Data Scientists; ML Engineers; Data Engineers; Expert users; Product teams; Engineering teams; Multi-functionally
Communication Scope
Communicate insights; Translate complex analytics; Actionable recommendations; Diverse collaborators
Process & Methodology
Roadmaps
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. Are you curious, high velocity, and ready to solve complex problems? Do you dream in data science and machine learning models? If so, we want you to join us! Our mission is to enable to deliver industry-winning machine learning 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 pipelines to execute machine learning models. You will collaborate with Data Scientists, ML Engineers, 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:** * Analyze large datasets to uncover patterns, trends, and insights that inform and improve machine learning models. * Design, build, and continuously refine ML models to address business challenges and enhance product capabilities. * Stay ahead of advancements in AI/ML and integrate emerging techniques into the MLOps lifecycle. * Build and maintain robust, scalable data pipelines and infrastructure to support model training and deployment. * Collaborate on data preprocessing and feature engineering to improve input data quality and model performance. * Design and optimize data architectures across cloud platforms (Snowflake, GCP, Azure) for AI/ML use cases. * Develop custom applications and implement CI/CD pipelines to support efficient ML solution deployment. * Deploy, evaluate, and monitor models in prod
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