Senior, Machine Learning Engineer

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(USA) | Sunnyvale | Full-time

$143k–$286k / yr

Posted: 5 days ago

Apply before:
December 11, 2026

More than 60 years ago, Sam Walton opened the first Walmart in Rogers, Arkansas. Today, we’re a people‑led, tech‑powered omnichannel retailer dedicated to helping people save money and live better all around the world.

Our 2.1 million associates are the engine behind what we do — serving customers and members in communities spanning 19 countries, in stores and clubs, online and through a supply chain built for speed and scale.

We’re committed to creating clear pathways for associates to learn, grow and advance. Whether you’re starting your first job or bringing years of experience, you’ll find room to grow, learn new skills and build a career with purpose. We’re proud to invest in our people and foster a culture grounded in respect, integrity, service and striving for excellence.

Recognized as a Fortune 100 Best Companies to Work For® (2025) and Great Place To Work®-Certified™, we’re proud of what we’re building together.

The Senior Machine Learning Engineer will lead the design, development, and deployment of scalable machine learning solutions that address complex business challenges, with a primary focus on building auto‑research capabilities that automate model training optimization, experimentation, and evaluation to accelerate the ML development lifecycle. This role requires collaboration with cross‑functional teams to deliver robust, production‑ready models and data pipelines while ensuring compliance with security and governance standards.

Additionally, they will provide technical leadership, mentor peers, and drive continuous improvement to enhance system reliability and innovation aligned with organizational goals.

Our team develops foundational models tailored for Walmart’s e‑commerce platform by leveraging large‑scale user interactions to create rich representations of users, products, and search queries. These models enable scalable search, advertising, recommendation, and personalization solutions. Team members apply expertise in data science, machine learning, and software engineering to optimize model performance, training, and deployment. With a strong focus on data quality, advanced analytics, and impactful visualization, the team delivers actionable insights that influence key business outcomes.

Cross‑functional collaboration drives innovation and continuous improvement in a dynamic technology environment.

• Collaborate with engineers, data scientists, and product teams to deliver machine learning features and models.
• Design and develop auto‑research capabilities that automate model training, optimization, experimentation, and evaluation, enabling AI agents to iteratively tune hyperparameters and run experiments against defined objective metrics.
• Surface the best‑performing models with minimal manual intervention, accelerating the overall 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, to sustain performance.
• Conduct rigorous model evaluation, monitoring, and maintenance to address model drift and performance issues.
• Ensure secure, compliant machine learning engineering aligned with enterprise AI governance standards.

• Proven expertise in designing, developing, and deploying scalable machine learning systems using frameworks such as Tensor Flow, PyTorch, and Scikit‑learn.
• Strong proficiency in programming languages including Python, SQL, Java, and C++ to build production‑ready…