Senior ML Engineer: Generative AI & Production Systems

Micron Technology, Inc.; Boise (ID); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical/Dental/Vision plans

Paid time off

Paid holidays

Paid family leave

Job summary

Micron Technology, Inc. is seeking a Data/Solution Pipeline Engineer to design, deploy and optimize enterprise-grade ML systems in cloud environments, enabling scalable data infrastructure for model training and deployment.

You will collaborate with Product and Engineering teams to implement data preprocessing, feature engineering, RAG techniques, and Generative AI capabilities, using Snowflake, GCP, Azure, Kubernetes, and CI/CD pipelines.

Qualifications

• Experience designing enterprise-grade end-to-end ML systems in cloud environments.
• Proficiency with regression, classification, deep learning, reinforcement learning, and generative AI.
• Experience with event-driven pipelines using Pub/Sub, Solace, or Kafka.
• Proficient with Docker and Kubernetes.
• ETL/ELT pipelines with Kubeflow, Dataflow, or Airflow.
• Strong SQL skills and API development for ML models.

Responsibilities

• Design, implement, and iterate on machine learning models for business challenges.
• Build and optimize data preprocessing and feature engineering for training.
• Deploy ML models to production with monitoring and cost optimization.
• Collaborate with Product/Engineering to apply Generative AI capabilities.
• Create CI/CD pipelines for ML solutions in cloud environments.

Skills

Data engineering

Machine Learning

Python

Cloud platforms

Snowflake

GCP

Azure

Docker

Kubernetes

ETL/ELT

SQL

RESTful APIs

RAG

Prompt engineering

LLMs

CI/CD

Monitoring

Production ML

Education

Master’s degree in Computer Science / ML / DS / Statistics / IE

Bachelor’s degree in Computer Science / ML / DS / Statistics / IE

Tools

Kubeflow

Dataflow

Airflow

Pub/Sub

Kafka

Snowflake

GCP

Azure

Docker

Kubernetes

Job description

Micron Technology, Inc. is seeking a Data/Solution Pipeline Engineer to design, deploy and optimize enterprise-grade ML systems in cloud environments, enabling scalable data infrastructure for model training and deployment.

You will collaborate with Product and Engineering teams to implement data preprocessing, feature engineering, RAG techniques, and Generative AI capabilities, using Snowflake, GCP, Azure, Kubernetes, and CI/CD pipelines.