(USA) Principal, Machine Learning Engineer

Walmart•Sunnyvale, CA

3d•Onsite

About The Position

The Principal, Machine Learning Engineer will lead the design and development of scalable, production-grade ML systems that address complex business challenges. This role involves architecting end-to-end ML pipelines, driving innovation in advanced modeling techniques, and ensuring robust deployment and monitoring practices. The position requires collaboration with cross-functional teams to align ML solutions with organizational goals while mentoring technical staff and promoting engineering excellence. The successful candidate will apply sound technical judgment, foster continuous improvement, and contribute to Walmart’s reputation through technical leadership and knowledge sharing. About the team: The International Recommendations Platform team develops a multi-tenant framework delivering personalized experiences across Walmart International sites. The team pioneers innovation in Machine Learning and AI to improve customer engagement and business outcomes. Utilizing cloud-native architecture and software design patterns, members build scalable, resilient solutions. Collaboration is key, focusing on API design, system reviews, and data-driven decisions. The team emphasizes continuous improvement through DevOps engineering and software prototyping, ensuring accelerated delivery and high-quality standards in a dynamic environment. This environment fosters technical excellence and impactful innovation.

Requirements

Extensive experience designing and architecting scalable, production-grade machine learning systems aligned with business objectives.
Proficiency in ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and programming languages including Python, Java, and SQL.
Expertise in end-to-end ML lifecycle management, including data sourcing, feature engineering, model training, deployment, and monitoring.
Strong background in advanced modeling techniques, including deep learning, NLP, reinforcement learning, and time series analysis.
Demonstrated ability to lead technical strategy, mentor engineers, and influence cross-functional collaboration.
Skilled in ML model validation, hyperparameter optimization, and MLOps best practices.
Excellent critical thinking and technical writing capabilities to communicate complex concepts clearly.
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.
OR 7 years’ experience in software engineering, machine learning engineering, AI systems or related area.
2 years’ supervisory experience.

Nice To Haves

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.

Responsibilities

Architect and guide the development of scalable, production-grade machine learning systems integrated into customer-facing and operational products.
Lead end-to-end ML lifecycle execution, including data sourcing, feature engineering, model training, deployment, and monitoring.
Drive innovation in applied ML through advanced modeling techniques such as deep learning, NLP, reinforcement learning, and multimodal approaches.
Mentor engineering teams, influence architectural decisions, and promote technical excellence across ML disciplines.
Collaborate cross-functionally to align ML solutions with platform strategies and ensure seamless integration with downstream applications.
Establish standards for model evaluation, fairness, and responsible AI compliance.
Publish technical insights and contribute to Walmart’s engineering knowledge base.