Senior, Machine Learning Engineer

Walmart; Sunnyvale (CA); Presencial; USD 143.000 - 286.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health benefits

401(k) & stock purchase

Paid time off

Disability benefits

Education benefit: Live Better U

Education expenses covered

Descripción de la vacante

Walmart in Sunnyvale, CA is seeking an experienced ML Engineer to design and deliver scalable machine learning systems. You will partner with engineers, data scientists, and product teams to deliver ML features and models, and build auto-research capabilities that automate training, optimization, experimentation, and evaluation.

You will enable iterative hyperparameter tuning and monitor objective metrics, surfacing top models with minimal manual intervention to accelerate ML development and

Formación

• Experience designing, developing, and deploying scalable ML systems using TensorFlow, PyTorch, Scikit-learn.
• Strong programming skills in Python, SQL, Java, and C++ for production-ready ML apps.
• Hands-on experience operating agentic or autonomous research systems.

Responsabilidades

• Partner with engineers, data scientists, and product teams to deliver ML features and models.
• Design and build auto-research capabilities that automate model training, optimization, experimentation, and evaluation.
• Enable iterative hyperparameter tuning and experiment execution against defined objective metrics.
• Identify and surface best-performing models with minimal manual intervention to speed up ML lifecycle.

Conocimientos

TensorFlow

PyTorch

Scikit-learn

Python

SQL

Java

C++

AutoResearch

MLOps

CI/CD

Telemetry

Educación

Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or related area

5 years’ experience in software engineering, machine learning engineering, AI systems, or related area

Herramientas

CI/CD

AutoResearch

Telemetry

Descripción del empleo

Design and deliver scalable machine learning systems with a focus on automated model training optimization and experimentation for enterprise AI governance.

Responsibilities

• Partner with engineers, data scientists, and product teams to deliver machine learning features and models.
• Design and build auto-research capabilities that automate model training, optimization, experimentation, and evaluation.
• Enable iterative hyperparameter tuning and experiment execution against defined objective metrics.
• Identify and surface best-performing models with minimal manual intervention to speed up the machine learning development lifecycle.
• Implement, test, and support machine learning services, APIs, and data pipelines to maintain quality and reliability.
• Apply MLOps practices including CI/CD, model versioning, and automated retraining to sustain performance.
• Perform rigorous evaluation, monitoring, and maintenance to address model drift and performance issues.
• Ensure secure, compliant machine learning aligned with enterprise AI governance standards.

Requirements

• Experience designing, developing, and deploying scalable machine learning systems using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong programming skills in Python, SQL, Java, and C++ for production-ready machine learning applications.
• Hands‑on experience operating agentic or autonomous research systems.
• Experience running automated experimentation against defined objective metrics through AutoResearch loops.
• Knowledge of the end-to-end machine learning lifecycle: data sourcing, feature engineering, model training, evaluation, deployment, and monitoring.
• MLOps knowledge including CI/CD, model versioning, automated retraining, and telemetry for reliability.
• Ability to implement secure, compliant machine learning pipelines that align with enterprise AI governance standards.
• Demonstrated collaboration and mentorship within cross-functional teams to drive technical excellence.

Technologies

• TensorFlow, PyTorch, Scikit-learn
• Python, SQL, Java, C++
• CI/CD, AutoResearch, telemetry

Education & Experience

• Minimum experience: 3 years.
• Minimum qualifications (Option 1): Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or related area, plus 3 years’ experience in software engineering, machine learning engineering, AI systems, or related area.
• Minimum qualifications (Option 2): 5 years’ experience in software engineering, machine learning engineering, AI systems, or related area.

Preferred Qualifications

• Master’s degree in a related field and 1 year’s experience in software engineering, machine learning engineering, AI systems, or related area.
• Prior experience with accessibility best practices.

  Preferred Qualifications

  • Prior experience creating inclusive digital experiences, including knowledge of implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA, assistive technologies, and integrating accessibility into digital experiences.

  Benefits

  • Health benefits: medical, vision, and dental coverage.
  • Financial benefits: 401(k), stock purchase, and company-paid life insurance.
  • Paid time off: PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting.
  • Other benefits: short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.
  • Live Better U: Walmart-paid education benefit program for full-time and part‑time associates in Walmart and Sam’s Club facilities.
  • Tuition, books, and fees are paid by Walmart.

  Work Location

  • Sunnyvale, CA, United States (onsite)
  • Primary location: 815 Eleventh Ave, Sunnyvale, CA 94089-4731, United States of America

  Salary: USD 143,000 - 286,000 per year.

  About the Team

  • Develops foundational models for Walmart’s e-commerce platform using large-scale user interactions to create representations of users, products, and search queries.
  • Supports scalable search, advertising, recommendation, and personalization solutions.
  • Applies data science, machine learning, and software engineering to optimize model performance, training, and deployment.
  • Focuses on data quality, advanced analytics, and impactful visualization to deliver actionable insights that influence key business outcomes.
  • Leverages cross-functional collaboration for innovation and continuous improvement in a dynamic technology environment.