2 months ago
Base Salary
$156k - $338k/yr
Responsibilities
- Architect and lead scalable, production-grade ML systems for customer-facing personalization and recommendation experiences.
- Own technical direction across data and feature pipelines, model training, evaluation, deployment, inference, serving, monitoring, retraining, and lifecycle management.
- Design high-performance batch and real-time ML architectures balancing quality, latency, throughput, scalability, reliability, maintainability, and cost.
- Translate model prototypes and experimentation into scalable, maintainable production systems with Data Scientists and ML practitioners.
- Establish engineering practices for deployment, feature management, reproducibility, automated testing, observability, model performance monitoring, and drift detection.
- Build reusable ML capabilities, services, and infrastructure that accelerate adoption across teams.
- Define technical strategies for complex ML problems and influence architecture and engineering decisions across multiple teams.
- Mentor senior technical talent, raise engineering standards, and provide technical leadership across the ML engineering community.
Requirements
- Bachelor’s degree in computer science, computer engineering, computer information systems, software engineering, or a related area plus five years of relevant experience, or seven years of relevant experience without the degree requirement.
- Two years of supervisory experience.
- Extensive experience designing, building, deploying, and operating large-scale machine learning systems in production.
- Strong software engineering fundamentals and proficiency in Python.
- Experience with production ML frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or comparable technologies.
- Expertise in recommendation and ranking, deep learning, representation learning, NLP, reinforcement learning, or related advanced ML techniques.
- Experience designing scalable batch or real-time training, inference, and feature-serving architectures.
- Understanding of distributed systems, APIs and services, cloud-native architectures, and scalable data processing.
- Experience with ML pipelines, CI/CD, model and data versioning, testing, observability, performance monitoring, and drift detection.
- Experience deploying production ML systems on cloud platforms such as GCP or Azure.
- Ability to establish technical direction, influence architecture, drive complex initiatives, mentor engineers, and communicate complex concepts clearly.
- Preferred qualifications include a master’s degree in a relevant field plus three years of relevant experience, accessibility best practices, inclusive digital experiences, WCAG 2.2 AA, and assistive technologies.
Benefits
- Medical, vision, and dental coverage.
- 401(k), stock purchase benefits, and company-paid life insurance.
- Paid time off, including sick leave, parental leave, family care leave, bereavement, jury duty, and voting leave.
- Short-term and long-term disability, company discounts, Military Leave Pay, and adoption and surrogacy expense reimbursement.
- PTO and/or PPTO may be used for vacation, sick leave, holidays, or other purposes, subject to classification and tenure.
- Walmart-paid education benefits through Live Better U, including tuition, books, and fees for eligible programs from high school completion through bachelor’s degrees and certificates.
- Annual or quarterly performance bonuses and possible stock compensation.
- The position is located in Sunnyvale, California or Bellevue, Washington.
Tech Stack
Categories
About Walmart
Walmart is a global omnichannel retailer that sells groceries, general merchandise, and services through Walmart and Sam's Club stores and online marketplaces for consumers and small businesses. Its model spans physical retail, e-commerce, advertising, and a vast supply chain, plus pharmacy, health, and financial services. Founded in 1962 and headquartered in Bentonville, Arkansas, Walmart Inc. is a public company on the NYSE (WMT) operating in the U.S. and multiple international markets.