Walmart
Position Summary
We are seeking a highly motivated Machine Learning Engineer to join our Data Science team. In this role, you will design, develop, and deploy machine learning models at scale while shaping next‑generation AI/ML and GenAI products that help our suppliers grow their business.
What You’ll Do
Infrastructure & MLOps
Build and maintain end‑to‑end ML infrastructure for data ingestion, feature engineering, training, deployment, and monitoring.
Develop tools and frameworks that streamline experimentation for data scientists.
Ensure best practices in MLOps: CI/CD for ML, automated retraining, model versioning, and monitoring.
Optimize system performance, reliability, and cost efficiency in production environments.
Collaboration & Leadership
Partner with data scientists to move research prototypes into robust, scalable systems.
Collaborate with platform and infrastructure engineers to optimize compute, storage, and deployment efficiency.
Advocate for ML engineering best practices and scalable design patterns.
Mentor junior engineers and data scientists on production readiness and infrastructure use.
ML Systems / Recommendation Systems
Enable design, train, and deploy ML models or recommendation systems (ranking, retrieval, embeddings, personalization).
Collaborate with data scientists to bring prototypes into production.
Agentic AI Enablement
Integrate recommendation outputs into a centralized agentic AI system to enhance reasoning and decision‑making.
Support workflows such as planning, contextual decision‑making, and multi‑agent coordination.
What You Will Bring
Bachelor’s/Master’s/Ph.D. in Computer Science, Machine Learning, or a related field.
Strong expertise in MLOps and infrastructure engineering (CI/CD, monitoring, automation, Docker/Kubernetes, cloud ML platforms).
Experience with cloud platforms (e.g., AWS, Azure, GCP).
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit‑learn), plus experience with distributed data/compute systems.
Experience building real‑time and batch‑processed inference systems.
Strong understanding of data structures, algorithms, and statistical modeling.
Experience with data preprocessing, feature engineering, ML training, and model evaluation.
Experience with pipeline optimization (multi‑processing, multi‑threading, distributed frameworks, caching, etc.).
Excellent problem‑solving and analytical skills.
Strong communication and collaboration skills.
Preferred Skills
Hands‑on experience building and deploying ML systems at scale.
Familiarity with LLMs, reinforcement learning, or agentic AI frameworks.
Prior experience in creating scalable ML platforms.
Benefits
Competitive base salary range: $117,000.00–$234,000.00 (Sunnyvale, CA) or $90,000.00–$180,000.00 (Bentonville, AR).
Annual or quarterly performance bonuses.
Stock options.
Health, vision, and dental coverage.
401(k) plan with company match.
PTO, parental leave, family care leave, bereavement, jury duty, and voting.
Short‑term and long‑term disability coverage.
Company discounts.
Location 1345 Crossman Ave, Sunnyvale, CA 94089‑1114, United States of America.
Minimum Qualifications Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or related area and 3 years’ experience in software engineering or related area.
Option 2: 5 years’ experience in software engineering or related area.
Preferred Qualifications
Master’s degree in Computer Science, Computer Engineering, Computer Information Systems, Software Engineering, or related area and 1 year’s experience in software engineering or related area. We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.
EEO and Workplace Safety Walmart and its subsidiaries are committed to maintaining a drug‑free workplace and has a no‑tolerance policy regarding the use of illegal drugs and alcohol on the job.
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What You’ll Do
Infrastructure & MLOps
Build and maintain end‑to‑end ML infrastructure for data ingestion, feature engineering, training, deployment, and monitoring.
Develop tools and frameworks that streamline experimentation for data scientists.
Ensure best practices in MLOps: CI/CD for ML, automated retraining, model versioning, and monitoring.
Optimize system performance, reliability, and cost efficiency in production environments.
Collaboration & Leadership
Partner with data scientists to move research prototypes into robust, scalable systems.
Collaborate with platform and infrastructure engineers to optimize compute, storage, and deployment efficiency.
Advocate for ML engineering best practices and scalable design patterns.
Mentor junior engineers and data scientists on production readiness and infrastructure use.
ML Systems / Recommendation Systems
Enable design, train, and deploy ML models or recommendation systems (ranking, retrieval, embeddings, personalization).
Collaborate with data scientists to bring prototypes into production.
Agentic AI Enablement
Integrate recommendation outputs into a centralized agentic AI system to enhance reasoning and decision‑making.
Support workflows such as planning, contextual decision‑making, and multi‑agent coordination.
What You Will Bring
Bachelor’s/Master’s/Ph.D. in Computer Science, Machine Learning, or a related field.
Strong expertise in MLOps and infrastructure engineering (CI/CD, monitoring, automation, Docker/Kubernetes, cloud ML platforms).
Experience with cloud platforms (e.g., AWS, Azure, GCP).
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit‑learn), plus experience with distributed data/compute systems.
Experience building real‑time and batch‑processed inference systems.
Strong understanding of data structures, algorithms, and statistical modeling.
Experience with data preprocessing, feature engineering, ML training, and model evaluation.
Experience with pipeline optimization (multi‑processing, multi‑threading, distributed frameworks, caching, etc.).
Excellent problem‑solving and analytical skills.
Strong communication and collaboration skills.
Preferred Skills
Hands‑on experience building and deploying ML systems at scale.
Familiarity with LLMs, reinforcement learning, or agentic AI frameworks.
Prior experience in creating scalable ML platforms.
Benefits
Competitive base salary range: $117,000.00–$234,000.00 (Sunnyvale, CA) or $90,000.00–$180,000.00 (Bentonville, AR).
Annual or quarterly performance bonuses.
Stock options.
Health, vision, and dental coverage.
401(k) plan with company match.
PTO, parental leave, family care leave, bereavement, jury duty, and voting.
Short‑term and long‑term disability coverage.
Company discounts.
Location 1345 Crossman Ave, Sunnyvale, CA 94089‑1114, United States of America.
Minimum Qualifications Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or related area and 3 years’ experience in software engineering or related area.
Option 2: 5 years’ experience in software engineering or related area.
Preferred Qualifications
Master’s degree in Computer Science, Computer Engineering, Computer Information Systems, Software Engineering, or related area and 1 year’s experience in software engineering or related area. We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.
EEO and Workplace Safety Walmart and its subsidiaries are committed to maintaining a drug‑free workplace and has a no‑tolerance policy regarding the use of illegal drugs and alcohol on the job.
#J-18808-Ljbffr