Staff Machine Learning Engineer

Analyze existing 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. Build knowledge by keeping up with the latest advancements in machine learning and artificial intelligence (AI), integrating new techniques and technologies into our MLOPS development process. Build and maintain Data/Solution Pipeline to ensure a robust and scalable data infrastructure that supports the training and deployment of machine learning models. Collaborate on data preprocessing and feature engineering to enhance the quality of input data for machine learning models. Build custom software components and analytics applications. Create/Maintain CI/CD pipelines of machine learning solutions in the cloud environment. Implement strategies for deploying machine learning models into production environments. Responsible for selecting the 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. Collaborate with the Product and Engineering teams to identify opportunities for integrating machine learning and Generative artificial intelligence capabilities into Project solutions/platform. Collaborate with the Product team to design a Tactical roadmap for the adoption of machine learning technologies, paradigms & frameworks following organizational best practices. Work in a technical team through development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics using machine learning and artificial intelligence. Build enterprise-grade applications leveraging Generative AI technologies, including large language models (LLMs), multimodal architectures, and advanced prompt engineering. Fine-tune pre-trained models on domain-specific datasets, Implement retrieval-augmented generation (RAG) for knowledge grounding, and build agentic systems that orchestrate autonomous workflows and integrate with domain-specific APIs. May telecommute part-time., 1. Building and executing end to end ML systems

1. TensorFlow, PyTorch, and scikit learn.
2. Prediction (regression) and classification algorithms; deep learning, reinforcement learning, and generative AI
3. Python or Java
4. Pub/Sub, Solace, or Kafka
5. Developing ML/AI solutions in GCP, Azure, or AWS
6. Docker and Kubernetes
7. Developing ETL/ELT pipelines using Kubeflow, Dataflow, or Airflow
8. SQL
9. Data structures and schemas
10. APIs to expose trained machine learning models for consumption
11. Building enterprise-grade applications using Generative AI technologies
12. Retrieval-Augmented Generation (RAG) for knowledge grounding and fine-tuning pre-trained models on domain-specific datasets
13. Designing and implementing agentic systems that orchestrate autonomous workflows and integrate with APIs

Employer will accept a Master’s degree in Computer Science, Machine Learning, Data Science, Statistics, or related field and 3 years of experience in the job offered or in a related occupation.

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.