Walmart
Position Summary
Design and deliver scalable, production‑grade ML solutions for Walmart, leading architecture, implementation, and operations across cloud environments. Responsibilities
ML System Architecture & Delivery
– Lead the design and implementation of scalable, production‑grade ML solutions that address business‑critical needs. Translate complex or ambiguous problem statements into clear technical requirements, architectural designs, and success metrics. Select and integrate appropriate ML frameworks (Scikit‑lean, TensorFlow, PyTorch, XGBoost, Spark ML) and coding languages (Python, SQL, Java, C++, R) to meet performance, explainability, and maintainability standards. Drive platform alignment by ensuring solutions leverage and contribute to Walmart’s shared ML infrastructure and tooling. End‑to‑End ML Lifecycle Execution
– Oversee all phases of the ML lifecycle: data sourcing, feature engineering, model training, deployment, monitoring, and continuous improvement. Apply MLOps best practices such as CI/CD for ML, automated training pipelines, model versioning, and telemetry‑based monitoring. Implement robust evaluation frameworks for model performance, data quality, and fairness, ensuring compliance with responsible AI principles. ML Platform Engineering & Operations
– Build and maintain reusable infrastructure components, including feature stores, model runtimes, SDKs, and workflow orchestration systems. Manage large‑scale ML operations across cloud environments (AWS, GCP, Azure), leveraging containerization, Kubernetes, and workflow automation. Implement observability tooling to track model behavior, detect drift, and ensure high availability and low latency in production environments. Technical Leadership & Mentorship
– Provide hands‑on mentorship to engineers, guiding them through architectural decisions, implementation details, and debugging complex ML issues. Set and enforce engineering standards for code quality, testing, deployment, and operational excellence. Experimentation & Innovation
– Design and manage experimentation pipelines for hypothesis testing, A/B experiments, and continuous model iteration. Explore advanced techniques such as AutoML, neural architecture search, domain‑specific NLP tooling, and multimodal architectures to accelerate solution delivery. Share innovations and learnings through technical documentation, presentations, and cross‑team forums to elevate Walmart’s ML engineering practices. Qualifications
Minimum Qualifications Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field and 4 years of experience in software engineering, machine learning engineering, or AI systems. OR 6 years of experience in software engineering, machine learning engineering, or AI systems. Preferred Qualifications Master’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field and 2 years of experience in software engineering, machine learning engineering, or AI systems. Knowledge of accessibility best practices, including WCAG 2.2 AA standards and assistive technologies. Compensation
Annual salary range $169,000–$338,000. Additional compensation includes annual or quarterly performance bonuses and stock options. Location
1395 Crossman Ave, Sunnyvale, CA 94089‑1114, United States of America.
#J-18808-Ljbffr
Design and deliver scalable, production‑grade ML solutions for Walmart, leading architecture, implementation, and operations across cloud environments. Responsibilities
ML System Architecture & Delivery
– Lead the design and implementation of scalable, production‑grade ML solutions that address business‑critical needs. Translate complex or ambiguous problem statements into clear technical requirements, architectural designs, and success metrics. Select and integrate appropriate ML frameworks (Scikit‑lean, TensorFlow, PyTorch, XGBoost, Spark ML) and coding languages (Python, SQL, Java, C++, R) to meet performance, explainability, and maintainability standards. Drive platform alignment by ensuring solutions leverage and contribute to Walmart’s shared ML infrastructure and tooling. End‑to‑End ML Lifecycle Execution
– Oversee all phases of the ML lifecycle: data sourcing, feature engineering, model training, deployment, monitoring, and continuous improvement. Apply MLOps best practices such as CI/CD for ML, automated training pipelines, model versioning, and telemetry‑based monitoring. Implement robust evaluation frameworks for model performance, data quality, and fairness, ensuring compliance with responsible AI principles. ML Platform Engineering & Operations
– Build and maintain reusable infrastructure components, including feature stores, model runtimes, SDKs, and workflow orchestration systems. Manage large‑scale ML operations across cloud environments (AWS, GCP, Azure), leveraging containerization, Kubernetes, and workflow automation. Implement observability tooling to track model behavior, detect drift, and ensure high availability and low latency in production environments. Technical Leadership & Mentorship
– Provide hands‑on mentorship to engineers, guiding them through architectural decisions, implementation details, and debugging complex ML issues. Set and enforce engineering standards for code quality, testing, deployment, and operational excellence. Experimentation & Innovation
– Design and manage experimentation pipelines for hypothesis testing, A/B experiments, and continuous model iteration. Explore advanced techniques such as AutoML, neural architecture search, domain‑specific NLP tooling, and multimodal architectures to accelerate solution delivery. Share innovations and learnings through technical documentation, presentations, and cross‑team forums to elevate Walmart’s ML engineering practices. Qualifications
Minimum Qualifications Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field and 4 years of experience in software engineering, machine learning engineering, or AI systems. OR 6 years of experience in software engineering, machine learning engineering, or AI systems. Preferred Qualifications Master’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field and 2 years of experience in software engineering, machine learning engineering, or AI systems. Knowledge of accessibility best practices, including WCAG 2.2 AA standards and assistive technologies. Compensation
Annual salary range $169,000–$338,000. Additional compensation includes annual or quarterly performance bonuses and stock options. Location
1395 Crossman Ave, Sunnyvale, CA 94089‑1114, United States of America.
#J-18808-Ljbffr