Senior, Machine Learning Engineer

Position: (USA) Senior, Machine Learning Engineer
Reference: R-2665597

Posted:

Location:

Sunnyvale, CA, United States Salary: $143000 - $286000/year

Type:
Full time / Regular/Permanent Company:
Walmart Business Segment:
Home Office Role summary:
The Senior Machine Learning Engineer will lead the design, development, and deployment of scalable machine learning solutions that address complex business challenges. This role involves collaborating closely with cross-functional teams to deliver robust models, ensuring high-quality code, and maintaining reliable ML pipelines. The position requires expertise in model evaluation, MLOps practices, and secure AI engineering. The successful candidate will drive continuous improvement, mentor peers, and uphold technical excellence while aligning solutions with organizational goals and compliance standards.

This role demands strong problem-solving skills and a commitment to innovation and operational resilience. About the team:
The eCommerce Search team manages the full technology stack enabling product search and discovery across Walmart’s global eCommerce platforms. Supported by microservices, extensive data and feature pipelines, search engines, and ML-serving infrastructure, the team processes millions of daily queries. Key focus areas include query and intent understanding using NLP and deep learning, real-time autocomplete, complex retrieval methods, multi-phase ML ranking models, and data pipelines that feed search indices and analytics.

This team’s work directly influences how millions of customers locate products efficiently and effectively.
Our systems tackle:

Query & Intent Understanding - product type classification, intent recognition, and sequence tagging (NLP and deep learning)
Autocomplete — real-time query suggestions at low-latency

Retrieval — Complex query construction, faceted navigation, semantic and lexical retrieval

Ranking — multi-phase ML models (LTR/Neural) optimizing for customer satisfaction

Data & Feature Pipelines — feeding search indices, feature stores, and analytics platforms.

What you'll do:

Collaborate with engineers, data scientists, and product teams to deliver machine learning features and models aligned with business objectives.

Design, develop, and deploy scalable ML systems using appropriate algorithms, frameworks, and coding languages.

Implement and maintain data pipelines, APIs, and model components ensuring quality, security, and compliance.

Apply MLOps practices including CI/CD, model versioning, monitoring, and automated retraining to sustain performance.

Conduct rigorous model evaluation, validation, and performance monitoring to ensure accuracy and reliability.

Mentor team members on best practices, code quality, and model evaluation techniques.

Participate in architectural discussions to enhance system scalability and maintainability.

Build and optimize high-throughput, low-latency services, applying best practices around distributed systems, fault-tolerance, and concurrency

Run A/B experiments; measuring impact on search quality and business metrics

What you'll bring:

Proven expertise in designing, developing, and deploying scalable machine learning models using frameworks such as Tensor Flow, PyTorch, and Scikit-learn.

Strong programming skills in Python, SQL, Java, C++, or R, with experience writing clean, production-ready code.

Proficiency in MLOps practices including CI/CD pipelines, model versioning, automated retraining, and monitoring for performance and drift.

Experience with hyperparameter optimization, model evaluation, and feature engineering to ensure robust ML solutions.

Ability to collaborate effectively with cross-functional teams and mentor junior engineers.

Knowledge of secure, compliant AI engineering and data pipeline development.

Familiarity with…