Senior ML Engineer for AI Search & Scalable ML Systems

Walmart; Sunnyvale (CA); On-site; USD 143,000 - 286,000; Full time

Benefits offered by this job

Stock options

Education benefits

Paid time off

Job summary

Walmart is hiring a Senior Machine Learning Engineer to lead the design, development, and deployment of scalable ML solutions for eCommerce search and discovery. You will collaborate with cross-functional teams to deliver robust models, implement ML pipelines, and ensure compliance and security across systems.

The role focuses on model evaluation, MLOps practices, and continuous improvement while mentoring peers and aligning solutions with corporate goals.

Qualifications

• Degree in computer science, engineering, or related field with relevant ML experience.
• 5+ years of software or ML engineering experience in production systems.
• Experience with MLOps, CI/CD, monitoring, and retraining workflows.

Responsibilities

• Lead design, development, and deployment of scalable ML features for search and discovery.
• Collaborate with engineers, data scientists, and product teams to meet business goals.
• Build robust data pipelines, APIs, and model components ensuring quality and security.
• Apply MLOps practices including versioning, monitoring, and automated retraining.
• Conduct model evaluation, validation, and performance monitoring for reliability.
• Mentor peers and participate in architectural discussions for scalability.

Skills

ML model design

Python

TensorFlow

PyTorch

Scikit-learn

MLOps

SQL

Java/C++/R

GPU optimization

Education

Bachelor's in CS/CE/SE

Master’s degree (preferred)

Tools

TensorFlow

PyTorch

Scikit-learn

Git

Job description

Walmart is hiring a Senior Machine Learning Engineer to lead the design, development, and deployment of scalable ML solutions for eCommerce search and discovery. You will collaborate with cross-functional teams to deliver robust models, implement ML pipelines, and ensure compliance and security across systems.

The role focuses on model evaluation, MLOps practices, and continuous improvement while mentoring peers and aligning solutions with corporate goals.