Senior, Machine Learning Engineer

Design and deliver scalable machine learning systems with a focus on automated model training optimization and experimentation for enterprise AI governance.

Responsibilities

• Partner with engineers, data scientists, and product teams to deliver machine learning features and models.
• Design and build auto-research capabilities that automate model training, optimization, experimentation, and evaluation.
• Enable iterative hyperparameter tuning and experiment execution against defined objective metrics.
• Identify and surface best-performing models with minimal manual intervention to speed up the machine learning development lifecycle.
• Implement, test, and support machine learning services, APIs, and data pipelines to maintain quality and reliability.
• Apply MLOps practices including CI/CD, model versioning, and automated retraining to sustain performance.
• Perform rigorous evaluation, monitoring, and maintenance to address model drift and performance issues.
• Ensure secure, compliant machine learning aligned with enterprise AI governance standards.

Requirements

• Experience designing, developing, and deploying scalable machine learning systems using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong programming skills in Python, SQL, Java, and C++ for production-ready machine learning applications.
• Hands-on experience operating agentic or autonomous research systems.
• Experience running automated experimentation against defined objective metrics through AutoResearch loops.
• Knowledge of the end-to-end machine learning lifecycle: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring.
• MLOps knowledge including CI/CD, model versioning, automated retraining, and telemetry for reliability.
• Ability to implement secure, compliant machine learning pipelines that align with enterprise AI governance standards.
• Demonstrated collaboration and mentorship within cross-functional teams to drive technical excellence.

Technologies

• TensorFlow, PyTorch, Scikit-learn
• Python, SQL, Java, C++
• CI/CD, AutoResearch, telemetry

Education & Experience

• Minimum experience: 3 years.
• Minimum qualifications (Option 1): Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or related area, plus 3 years’ experience in software engineering, machine learning engineering, AI systems, or related area.
• Minimum qualifications (Option 2): 5 years’ experience in software engineering, machine learning engineering, AI systems, or related area.

Preferred Qualifications

• Master’s degree in a related field and 1 year’s experience in software engineering, machine learning engineering, AI systems, or related area.
• Prior experience with accessibility best practices.
• Prior experience creating inclusive digital experiences, including knowledge of implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA, assistive technologies, and integrating accessibility into digital experiences.

Benefits

• Health benefits: medical, vision, and dental coverage.
• Financial benefits: 401(k), stock purchase, and company-paid life insurance.
• Paid time off: PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting.
• Other benefits: short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.
• Live Better U: Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam’s Club facilities.
• Tuition, books, and fees are paid by Walmart.

Work Location

• Sunnyvale, CA, United States (onsite)
• Primary location: 815 Eleventh Ave, Sunnyvale, CA 94089-4731, United States of America

Salary: USD 143,000 - 286,000 per year.

About the Team

• Develops foundational models for Walmart’s e-commerce platform using large-scale user interactions to create representations of users, products, and search queries.
• Supports scalable search, advertising, recommendation, and personalization solutions.
• Applies data science, machine learning, and software engineering to optimize model performance, training, and deployment.
• Focuses on data quality, advanced analytics, and impactful visualization to deliver actionable insights that influence key business outcomes.
• Leverages cross-functional collaboration for innovation and continuous improvement in a dynamic technology environment.