About the team:
The Personalization team at Walmart is committed to enhancing customer experiences by delivering seamless, tailored journeys across all engagement channels. Operating at the nexus of vast product assortments, millions of customers, and thousands of stores, the team develops advanced AI-driven solutions that empower both customers and associates. Comprising data scientists, engineers, and product experts, the team designs and builds innovative machine learning models and systems using cutting-edge techniques such as deep learning, reinforcement learning, and natural language processing. Their work shapes the future of e-commerce by enabling personalized, efficient, and trusted interactions.What you'll do...
- Architect and lead the development of scalable, production-grade ML systems powering customer-facing personalization and recommendation experiences.
- Own technical direction across the end-to-end ML lifecycle, including data and feature pipelines, model training, evaluation, deployment, serving, monitoring, and continuous improvement.
- Design high-performance batch and real-time ML architectures capable of operating reliably at large scale.
- Partner with Data Scientists and other ML practitioners to translate model prototypes and experimentation into scalable, maintainable production systems.
- Establish engineering patterns and best practices for model deployment, feature management, reproducibility, automated testing, observability, retraining, and model lifecycle management.
- Develop and optimize ML solutions using techniques such as recommendation and ranking, deep learning, representation learning, NLP, and other advanced machine learning approaches.
- Design systems that balance model quality with production requirements such as latency, throughput, scalability, reliability, maintainability, and cost.
- Build reusable ML capabilities, services, and infrastructure that accelerate development and adoption across teams.
- Define technical strategies and architecture for complex and ambiguous ML problems and influence engineering decisions across multiple teams.
- Partner cross-functionally with ML, Software Engineering, Data Science, Product, and Platform teams to align ML capabilities with customer and business objectives.
- Mentor senior technical talent, raise engineering standards, and provide technical leadership across the broader ML engineering community.
- Extensive experience designing, building, deploying, and operating large-scale machine learning systems in production.
- Strong software engineering fundamentals and proficiency in Python and production software development practices.
- Deep understanding of the end-to-end ML lifecycle, including data preparation, feature engineering, model development, training, evaluation, deployment, inference, monitoring, and retraining.
- Experience building production ML systems using frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or comparable technologies.
- Expertise in one or more relevant ML domains such as recommendation and ranking, deep learning, representation learning, NLP, reinforcement learning, or related advanced ML techniques.
- Experience designing scalable batch and/or real-time model training, inference, and feature-serving architectures.
- Strong understanding of distributed systems, APIs and services, cloud-native architectures, and scalable data processing.
- Experience with production ML engineering practices including automated pipelines, CI/CD, model and data versioning, testing, observability, model performance monitoring, and drift detection.
- Experience designing ML systems for performance, reliability, scalability, latency, and cost efficiency.
- Experience building and deploying production ML systems on cloud platforms such as GCP, Azure, or comparable environments, including scalable training, inference, and ML pipelines.
- Demonstrated ability to establish technical direction, influence architecture across teams, and drive complex initiatives from concept through production.
- Proven ability to mentor engineers, establish engineering best practices, and raise technical standards across an organization.
- Strong technical communication skills with the ability to communicate complex ML and engineering concepts clearly to technical and non-technical stakeholders.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
Sunnyvale, California US-11349: The annual salary range for this position is $169,000.00 - $338,000.00
Bellevue, Washington US-11663: The annual salary range for this position is $156,000.00 - $312,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock
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Minimum Qualifications...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 5 years’ experience in software engineering, machine learning engineering, AI systems or related area.Option 2: 7 years’ experience in software engineering, machine learning engineering, AI systems or related area.
2 years’ supervisory experience.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 3 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.Primary Location...1395 Crossman Ave, Sunnyvale, CA 94089-1114, United States of AmericaWalmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.Skills Required
- Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or a related area, plus 5 years of experience in software engineering, machine learning engineering, AI systems, or a related area
- Alternatively, 7 years of experience in software engineering, machine learning engineering, AI systems, or a related area
- 2 years of supervisory experience
- Extensive experience designing, building, deploying, and operating large-scale machine learning systems in production
- Strong software engineering fundamentals and proficiency in Python
- Experience with production ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or XGBoost
- Experience designing scalable batch or real-time model training, inference, and feature-serving architectures
- Experience with distributed systems, APIs and services, cloud-native architectures, and scalable data processing
- Experience with production ML practices including automated pipelines, CI/CD, versioning, testing, observability, performance monitoring, and drift detection
- Experience deploying production ML systems on cloud platforms such as GCP or Azure
- Demonstrated ability to establish technical direction, influence architecture, and drive complex initiatives through production
- Proven ability to mentor engineers and establish engineering best practices
- Strong technical communication skills
- Master's degree in computer science, computer engineering, computer information systems, software engineering, or a related area
- Prior experience with accessibility best practices and inclusive digital experiences, including WCAG 2.2 AA and assistive technologies
Walmart Global Tech Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Walmart Global Tech and has not been reviewed or approved by Walmart Global Tech.
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Strong & Reliable Incentives — Compensation packages typically include base pay, performance bonuses, and stock awards, with access to an employee stock purchase plan. Feedback suggests annual bonus structures and stock grants are a consistent part of total compensation in many roles.
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Retirement Support — Retirement offerings include a company 401(k) match and stock purchase options that support long‑term savings. Feedback suggests these programs are a notable strength within the overall package.
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Parental & Family Support — Family benefits feature paid parental leave and adoption assistance, alongside tax‑advantaged accounts for healthcare spending. Feedback suggests these supports contribute meaningfully to perceived total rewards value.
Walmart Global Tech Insights
What We Do
Walmart has a long history of transforming retail and using technology to deliver innovations that improve how the world shops and empower our 2.2 million associates. It began with Sam Walton and continues today with Global Tech associates working together to power Walmart and lead the next retail disruption. We’re a high-performing, primarily virtual workforce that is human-led and tech-empowered. Our world-class software engineers, data scientists and engineers, cybersecurity professionals, product managers and business service professionals work with top talent on cutting-edge technologies that create unique and innovative experiences for our associates, customers and members across Walmart, Sam’s Club and Walmart International. At Walmart Global Tech, one line of code or bold idea can make life easier for hundreds of millions of people – talk about epic impact at a global scale.







