Senior Engineer, ML, SMAI
Boise, ID, US
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingBuild and maintain data pipelines that feed training and deployment of ML models
Design, implement, and iterate on machine learning models for business problems
Deploy ML models to production and monitor their performance
Build enterprise generative AI applications using LLMs, RAG and fine-tuning
Create and maintain CI/CD pipelines for ML solutions in the cloud
From the employer’s posting
Build and maintain Data/Solution Pipeline Engineering
Design, implement, and iterate on machine learning models to address specific business challenges
Design & Implement strategies for deploying machine learning models into production environments.
Design, develop, and deploy enterprise-grade applications leveraging Generative AI technologies, including large language models (LLMs), multimodal architectures, and advanced prompt engineering.
Create/Maintain CI/CD pipelines of machine learning solutions in the cloud environment.
Tools in this posting
- SQL
- Azure
- Docker
- GCP
- Kafka
- Kubernetes
- Snowflake
Source — Tool mentions in context
5\. ETL/ELT pipelines with Kubeflow, Dataflow, or Airflow 6\. SQL 7\. API development (RESTful APIs) for machine learning models
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. Build and maintain Data/Solution Pipeline Engineering to ensure a robust and scalable data infrastructure that supports the training and deployment of machine learning models. Analyze existing Micron data sets to identify patterns, trends, and insights that can enhance machine learning model development. Design, implement, and iterate on machine learning models to address specific business challenges and enhance product functionality. Collaborate on data preprocessing and feature engineering to enhance the quality of input data for machine learning models. Design and optimize data structures in data management systems (Cloud platforms - Snowflake, GCP, Azure) to enable AI/ML solutions. Build custom software components and analytics applications. Design & Implement strategies for deploying machine learning models into production environments. Responsible for selecting best model to meet both model performance and minimize compute costs. Establish and maintain monitoring systems to track the performance of deployed models and facilitate continuous improvement. Create/Maintain CI/CD pipelines of machine learning solutions in the cloud environment. Collaborate with the Product and Engineering teams to identify opportunities for integrating Generative artificial intelligence capabilities into Project solutions/platform. Collaborate with the Product team to design a Tactical roadmap for the adoption of Generative AI Technologies, paradigms & frameworks following organizational best practices. Design, develop, and deploy enterprise-grade applications leveraging Generative AI technologies, including large language models (LLMs), multimodal architectures, and advanced prompt engineering. Responsibilities include fine-tuning pre-trained models on domain-specific datasets, implementing retrieval-augmented generation (RAG) for knowledge grounding, and building agentic systems that orchestrate autonomous workflows and integrate with domain-specific APIs. Employer will accept a Master’s degree in Computer Science, Machine Learning, Data Science, Statistics, Industrial Engineering, or a related field and 1 year of experience in the job offered or related occupation. Alternatively, employer will accept a Bachelor’s degree in Computer Science, Machine Learning, Data Science, Statistics, Industrial Engineering, or a related field and 3 year of experience in the job offered or related occupation.
3\. Event-driven pipelines using Pub/Sub, Solace, or Kafka 4\. Docker and Kubernetes 5\. ETL/ELT pipelines with Kubeflow, Dataflow, or Airflow
2\. Regression and classification algorithms, deep learning, reinforcement learning, and generative AI 3\. Event-driven pipelines using Pub/Sub, Solace, or Kafka 4\. Docker and Kubernetes
Posting record
Report an errorActively hiringFirst seen by us 13 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 16, 2026 · 13 days ago
- Recorded sightings
- 58
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
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- Ask the employer about the pay range before committing time to the process.
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Boise, ID, US
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