(USA) Senior, Machine Learning Engineer

Walmart • Sunnyvale, CA

1d • $143,000 - $286,000 • Onsite

About The Position

The Senior Machine Learning Engineer leads the design, development, and deployment of scalable machine learning solutions for complex business challenges. The role focuses on building auto-research capabilities that automate model training optimization, experimentation, and evaluation, accelerating the machine learning development lifecycle. It works with cross-functional teams to deliver robust, production-ready models and data pipelines while meeting security and governance standards. The engineer also provides technical leadership, mentors peers, and drives continuous improvement in system reliability and innovation.

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. These models support search, advertising, recommendations, and personalization. The team combines data science, machine learning, and software engineering expertise, emphasizing data quality, advanced analytics, model performance, training, deployment, and cross-functional collaboration.

The position is based at Walmart’s Sunnyvale, California location. The annual salary range is $143,000 to $286,000, with additional annual or quarterly performance bonuses; certain positions may also include stock. The posting describes benefits including health coverage, financial benefits, paid time off, education assistance, and other programs.

Requirements

• Proven expertise designing, developing, and deploying scalable machine learning systems using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong proficiency in Python, SQL, Java, and C++ for building 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.
• Experience with the machine learning lifecycle, including data sourcing, feature engineering, model training, evaluation, deployment, and monitoring.
• Knowledge of MLOps practices such as CI/CD, model versioning, automated retraining, and telemetry.
• Ability to implement secure, compliant machine learning pipelines that adhere to enterprise AI governance standards.
• Demonstrated collaboration and mentorship capabilities within cross-functional teams.
• Option 1 minimum qualification: Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or a related area, and 3 years of experience in software engineering, machine learning engineering, AI systems, or a related area.
• Option 2 minimum qualification: 5 years of experience in software engineering, machine learning engineering, AI systems, or a related area.

Nice To Haves

• Master’s degree in computer science, computer engineering, computer information systems, software engineering, or a related area, and 1 year of experience in software engineering, machine learning engineering, AI systems, or a related area.
• Prior work experience in accessibility best practices.
• Prior work experience creating inclusive digital experiences, including knowledge of WCAG 2.2 AA standards, assistive technologies, and integrating digital accessibility.

Responsibilities

• Collaborate with engineers, data scientists, and product teams to deliver machine learning features and models.
• Design and develop auto-research capabilities to automate model training, optimization, experimentation, and evaluation, including AI-agent-driven hyperparameter tuning and experiments against defined objective metrics.
• Surface the best-performing models with minimal manual intervention to accelerate the machine learning development lifecycle.
• Implement, test, and support machine learning services, APIs, and data pipelines, ensuring quality and reliability.
• Apply MLOps practices, including CI/CD, model versioning, and automated retraining.
• Evaluate, monitor, and maintain models to address model drift and performance issues.
• Ensure machine learning engineering is secure, compliant, and aligned with enterprise AI governance standards.
• Provide technical leadership and mentor peers.
• Drive continuous improvement in system reliability and innovation.

Benefits

• Medical, vision, and dental coverage.
• 401(k).
• Stock purchase plan.
• Company-paid life insurance.
• Paid time off, including sick leave.
• Parental leave.
• Family care leave.
• Bereavement leave.
• Jury duty leave.
• Voting leave.
• Short-term and long-term disability.
• Company discounts.
• Military Leave Pay.
• Adoption and surrogacy expense reimbursement.
• PTO and/or PPTO usable for vacation, sick leave, holidays, or other purposes.
• Live Better U education benefit program, with tuition, books, and fees paid for eligible programs.
• Performance-based bonus awards, including annual or quarterly performance bonuses.
• Stock may be included as additional compensation for certain positions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior