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# (USA) Staff, Machine Learning Engineer

- **Company:** Wal-Mart Stores, Inc.
- **Location:** Sunnyvale, CA, United States
- **Experience:** Experienced
- **Salary:** $169,000.0 - $338,000.0
- **Contract:** Permanent contract
- **Skills:** Adobe Analytics, Amazon Web Services, Microsoft Azure, Cloud Computing, Software Quality, Computer Engineering, Continuous Integration, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, SQL Databases, Web Content Accessibility Guidelines, Google Cloud, Feature Engineering, Pytorch, Model Validation, Containerization, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, Software Version Control, Programming Languages
- **Published:** August 16, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3355987571&tx=JP5751FFL&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Proven expertise in designing and delivering scalable, production-grade machine learning solutions aligned with business needs.
 * Strong proficiency in ML frameworks such as TensorFlow, PyTorch, and Scikit-learn, and coding languages including Python and SQL.
 * Experience with end-to-end ML lifecycle management, including data sourcing, feature engineering, model training, deployment, and monitoring.
 * Knowledge of MLOps best practices, including CI/CD pipelines, model versioning, and telemetry-based monitoring.
 * Familiarity with cloud platforms (AWS, GCP, Azure), containerization, Kubernetes, and workflow automation.
 * Ability to implement robust model evaluation and validation frameworks.
 * Demonstrated leadership in mentoring engineers and enforcing engineering standards.
 * Strong collaboration and communication skills to work across teams and stakeholders., Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 4 years' experience in software engineering, machine learning engineering, AI systems or related area.

Option 2: 6 years' experience in software engineering, machine learning engineering, AI systems or related area.

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Master's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 2 years' experience in software engineering, machine learning engineering, AI systems or related area., Prior work experience in accessibility best practices., Prior work experience in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.

## Description

The Staff Machine Learning Engineer will lead the design and delivery of scalable, production-grade ML solutions that address critical business needs. This role involves overseeing the end-to-end ML lifecycle, including data sourcing, model development, deployment, and monitoring, while applying MLOps best practices. The engineer will build and maintain ML infrastructure, drive technical standards, and mentor team members. Collaboration across teams and continuous innovation are essential to advance Walmart's ML capabilities and ensure high-quality, reliable solutions that support business objectives and operational excellence., * Lead the design and deployment of scalable, production-grade machine learning solutions addressing critical business needs.

 * Translate complex problems into clear technical requirements, architectural designs, and measurable success criteria.
 * Oversee the full ML lifecycle, including data sourcing, feature engineering, model training, deployment, monitoring, and continuous improvement.
 * Implement MLOps best practices such as CI/CD pipelines, model versioning, and monitoring to ensure operational excellence.
 * Build and maintain reusable ML infrastructure components and manage large-scale operations across cloud environments using containerization and workflow automation.
 * Provide technical leadership and mentorship, setting standards for code quality, testing, and deployment.
 * Drive experimentation pipelines and explore advanced ML techniques to accelerate innovation and solution delivery.


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