Walmart
Senior Manager, Software Engineering - ML
Walmart, Sunnyvale, California, United States, 94087
Senior Manager, Software Engineering - ML
Senior Manager, Software Engineering - ML at Walmart.
As a Senior Engineering Manager on the Walmart International Search ML Infrastructure team, you will lead a team of data platform and ML engineers to build foundational platforms that power ML and search capabilities across all international markets.
Responsibilities
Provide guidance and lead a team of data platform engineers and ML engineers to build quality ML infrastructure solutions that process omni‑channel engagement data, serve ML models at scale, and enable sophisticated evaluation and experimentation frameworks.
Ensure Software Quality Engineering by keeping engineers up to date on best practices for ML operations, automated testing for data pipelines and ML systems, comprehensive monitoring and alerting, and taking a proactive approach to production ML infrastructure support.
Develop and implement ML platform development strategies using Agile practices and incremental delivery, collaborating across self‑organizing, cross‑functional teams.
Drive execution of multiple ML infrastructure initiatives and projects, identifying pain points, communicating technical roadmaps, removing barriers, and demonstrating adaptability to support continuous learning.
Work closely with data science teams, search engineering leads, international market stakeholders, and Product teams to align ML infrastructure with business objectives and accelerate model time‑to‑market.
Own end‑to‑end ML infrastructure, including parsers/stitchers for omni‑channel data, multi‑tenant data pipelines, feature engineering platforms, model serving infrastructure, evaluation systems, and experimentation frameworks.
Qualifications
Strong senior level engineering leadership expertise in medium to large technology companies with a focus on ML infrastructure, data platforms, or search systems.
12+ years total experience, including 8+ years in ML infrastructure, data platform engineering, or platform development with hands‑on technical contributions.
12+ years hands‑on experience with data pipeline technologies such as Apache Kafka, Apache Spark, Apache Flink, and Apache Airflow.
Expert‑level experience with ML model serving infrastructure (TensorFlow Serving, MLflow, Kubeflow), feature engineering platforms, and multi‑tenant ML operations at scale.
Extensive experience with containerization technology (Kubernetes, Docker), microservices architecture, and distributed computing for ML workloads.
Prior hands‑on development experience in Python, Java, or Scala for building data pipelines, ML serving systems, and evaluation frameworks at enterprise scale.
Deep technical knowledge of cloud platforms (AWS, GCP, Azure) focusing on ML services, managed data services, and infrastructure automation.
Proven experience in hiring and mentoring world‑class data engineering and ML engineering teams.
Leading large‑scale ML infrastructure systems in fast‑paced, multi‑market environments.
Experience with A/B testing frameworks, statistical analysis, search evaluation metrics (NDCG, MAP, MRR), and experimentation platforms.
Hands‑on experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) for data pipelines and ML systems.
Experience working in large, distributed teams using CI/CD for ML operations and Agile methodologies.
Excellent oral and verbal communication skills with the ability to collaborate across international markets and technical stakeholders.
BS or MS degree in Computer Science, Data Engineering, or a related technical field, and 12+ years of industry experience.
Minimum Qualifications
Bachelor’s degree in computer science or related field and 5 years’ experience in software engineering (or 7 years’ experience alone).
2 years of supervisory experience.
Preferred Qualifications
Master’s degree in computer science or related field and 3 years’ experience in software engineering.
Experience creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and digital accessibility integration.
About Walmart Global Tech Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. Walmart Global Tech is a team of software engineers, data scientists, cybersecurity experts, and service professionals at the world’s leading retailers, focused on innovation and technology.
Benefits Beyond a competitive compensation package, benefits include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and more.
Equal Opportunity Employer Walmart, Inc. is an Equal Opportunity Employer – By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions while being inclusive of all people.
Salary and Compensation Annual salary range: $143,000.00 – $286,000.00. Additional compensation includes annual or quarterly performance bonuses, and stock options may be available to eligible employees.
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As a Senior Engineering Manager on the Walmart International Search ML Infrastructure team, you will lead a team of data platform and ML engineers to build foundational platforms that power ML and search capabilities across all international markets.
Responsibilities
Provide guidance and lead a team of data platform engineers and ML engineers to build quality ML infrastructure solutions that process omni‑channel engagement data, serve ML models at scale, and enable sophisticated evaluation and experimentation frameworks.
Ensure Software Quality Engineering by keeping engineers up to date on best practices for ML operations, automated testing for data pipelines and ML systems, comprehensive monitoring and alerting, and taking a proactive approach to production ML infrastructure support.
Develop and implement ML platform development strategies using Agile practices and incremental delivery, collaborating across self‑organizing, cross‑functional teams.
Drive execution of multiple ML infrastructure initiatives and projects, identifying pain points, communicating technical roadmaps, removing barriers, and demonstrating adaptability to support continuous learning.
Work closely with data science teams, search engineering leads, international market stakeholders, and Product teams to align ML infrastructure with business objectives and accelerate model time‑to‑market.
Own end‑to‑end ML infrastructure, including parsers/stitchers for omni‑channel data, multi‑tenant data pipelines, feature engineering platforms, model serving infrastructure, evaluation systems, and experimentation frameworks.
Qualifications
Strong senior level engineering leadership expertise in medium to large technology companies with a focus on ML infrastructure, data platforms, or search systems.
12+ years total experience, including 8+ years in ML infrastructure, data platform engineering, or platform development with hands‑on technical contributions.
12+ years hands‑on experience with data pipeline technologies such as Apache Kafka, Apache Spark, Apache Flink, and Apache Airflow.
Expert‑level experience with ML model serving infrastructure (TensorFlow Serving, MLflow, Kubeflow), feature engineering platforms, and multi‑tenant ML operations at scale.
Extensive experience with containerization technology (Kubernetes, Docker), microservices architecture, and distributed computing for ML workloads.
Prior hands‑on development experience in Python, Java, or Scala for building data pipelines, ML serving systems, and evaluation frameworks at enterprise scale.
Deep technical knowledge of cloud platforms (AWS, GCP, Azure) focusing on ML services, managed data services, and infrastructure automation.
Proven experience in hiring and mentoring world‑class data engineering and ML engineering teams.
Leading large‑scale ML infrastructure systems in fast‑paced, multi‑market environments.
Experience with A/B testing frameworks, statistical analysis, search evaluation metrics (NDCG, MAP, MRR), and experimentation platforms.
Hands‑on experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) for data pipelines and ML systems.
Experience working in large, distributed teams using CI/CD for ML operations and Agile methodologies.
Excellent oral and verbal communication skills with the ability to collaborate across international markets and technical stakeholders.
BS or MS degree in Computer Science, Data Engineering, or a related technical field, and 12+ years of industry experience.
Minimum Qualifications
Bachelor’s degree in computer science or related field and 5 years’ experience in software engineering (or 7 years’ experience alone).
2 years of supervisory experience.
Preferred Qualifications
Master’s degree in computer science or related field and 3 years’ experience in software engineering.
Experience creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and digital accessibility integration.
About Walmart Global Tech Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. Walmart Global Tech is a team of software engineers, data scientists, cybersecurity experts, and service professionals at the world’s leading retailers, focused on innovation and technology.
Benefits Beyond a competitive compensation package, benefits include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and more.
Equal Opportunity Employer Walmart, Inc. is an Equal Opportunity Employer – By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions while being inclusive of all people.
Salary and Compensation Annual salary range: $143,000.00 – $286,000.00. Additional compensation includes annual or quarterly performance bonuses, and stock options may be available to eligible employees.
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