Sr Engineer, ML, SMAI

Micron Technology•Boise, ID

11d

About The Position

Micron Technology is seeking a Senior Machine Learning Engineer to build and maintain data and solution pipeline engineering that supports robust, scalable infrastructure for training and deploying machine learning models. The role analyzes Micron datasets for patterns and insights, develops and iterates on machine learning models for business challenges, and works on data preprocessing, feature engineering, and data structures across cloud platforms including Snowflake, GCP, and Azure. It also involves building software components and analytics applications, deploying models to production, selecting models that balance performance and compute costs, monitoring deployed models, and maintaining cloud-based ML CI/CD pipelines. The position collaborates with Product and Engineering teams to identify and plan opportunities for Generative AI adoption. It designs, develops, and deploys enterprise-grade applications using generative AI technologies, including LLMs, multimodal architectures, and prompt engineering. Work includes fine-tuning pretrained models on domain-specific datasets, implementing retrieval-augmented generation for knowledge grounding, and building agentic systems that coordinate workflows and integrate with domain-specific APIs.

Requirements

A master's degree in Computer Science, Machine Learning, Data Science, Statistics, Industrial Engineering, or a related field, plus 1 year of experience in the job offered or a related occupation; alternatively, a bachelor's degree in one of those fields, plus 3 years of experience in the job offered or a related occupation.
Experience with enterprise-grade, end-to-end machine learning systems in cloud environments.
Knowledge of regression and classification algorithms, deep learning, reinforcement learning, and generative AI.
Experience with event-driven pipelines using Pub/Sub, Solace, or Kafka.
Experience with Docker and Kubernetes.
Experience with ETL/ELT pipelines using Kubeflow, Dataflow, or Airflow.
SQL skills.
Experience developing RESTful APIs for machine learning models.
Knowledge of LLMs, multimodal models, prompt engineering, and agentic systems.
Experience with retrieval-augmented generation (RAG) and fine-tuning domain-specific models.
Experience with semiconductor manufacturing big data.

Responsibilities

Build and maintain data and solution pipeline engineering for scalable machine learning training and deployment infrastructure.
Analyze Micron datasets to identify patterns, trends, and insights that can improve machine learning model development.
Design, implement, and iterate on machine learning models to address business challenges and enhance product functionality.
Collaborate on data preprocessing and feature engineering to improve input data quality.
Design and optimize data structures in cloud data management systems, including Snowflake, GCP, and Azure.
Build custom software components and analytics applications.
Design and implement strategies for deploying machine learning models into production environments.
Select models that meet performance needs while minimizing compute costs.
Establish and maintain monitoring systems for deployed models and support continuous improvement.
Create and maintain cloud-based CI/CD pipelines for machine learning solutions.
Collaborate with Product and Engineering teams to identify opportunities to integrate generative AI into project solutions and platforms.
Collaborate with the Product team to design a tactical roadmap for adopting generative AI technologies, paradigms, and frameworks in accordance with organizational best practices.
Design, develop, and deploy enterprise-grade applications using LLMs, multimodal architectures, and advanced prompt engineering.
Fine-tune pretrained models on domain-specific datasets.
Implement retrieval-augmented generation for knowledge grounding.
Build agentic systems that orchestrate autonomous workflows and integrate with domain-specific APIs.