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Position Summary...
What you'll do...
Walmart’s Global Marketplace is one of the fastest-growing businesses inside the world's largest retailer. We run like a startup: small teams, high ownership, fast decisions.
Sellers don't need another dashboard that tells them what already happened. They need to know what to do next. This is an AI-first role. As Principal PM for Seller Growth, you'll build the AI that turns signals from shoppers, sellers, advertisers and account managers into recommendations sellers trust and act on. Those recommendations reach sellers directly and through the account managers who support them.
You'll own the whole loop: which signals matter, what we recommend, how sellers act, and whether it moved their GMV. You'll ship LLM-powered and agentic experiences, and you'll prove their impact with rigorous experimentation. Throughout, you'll grow sellers' sales without ever trading away their trust.
This is a hands-on IC role with org-wide reach. You'll launch products yourself, coach the PMs around you, and set the bar for how we build with AI.
About Team:
We are a high-ownership team focused on making Walmart Marketplace the best place for sellers to launch, build their brands, and achieve sustainable growth—while bringing customers a broader, stronger selection. Sellers face many choices as they build their businesses; our team turns those opportunities into clear, personalized, and prioritized plans they can act on through the tools and support they use every day. We are reimagining the seller experience with AI-powered guidance that makes it easier than ever to grow and succeed on Walmart Marketplace.
What you'll do:
Shape the vision and carry it forward.
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Work with leadership to define a bold vision for AI-powered seller growth.
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- Rally product, engineering, science and design teams around a shared set of priorities, and own the roadmap that makes it real across AI insights, recommendations and account-management tooling
- Connect the signals. Partner with Data Science and Engineering to combine omni-shopping and marketplace data into insights and recommendations that are relevant, explainable and trusted
- Multiply account managers. Give account teams AI tools that let them serve more sellers, with better outcomes, in less time
- Build with LLMs and agents. Take agentic features from prototype to global scale. Define how we evaluate quality, relevance and trust before and after launch
- Own the numbers, end to end. Track impact from recommendation adoption through seller retention to GMV. Design experiments that isolate causal impact, set decision criteria before tests run, and tell the story clearly to senior executives
- Lead through influence. Align senior executives across Growth, Account Management, Engineering, Data Science, Advertising, Operations and Design on one roadmap
What you'll bring:
- A seller-first mindset. You stay close to sellers, understand how they run their businesses, and translate their needs into products that help them grow.
- A strong experimentation mindset. You’ve led growth products where testing drives decisions. You can separate real signal from noisy results, compound incremental gains into meaningful growth, and recognize when a bold bet requires judgment rather than another test.
- Experience shipping AI products. You’ve taken LLM-powered or agentic capabilities from concept to production and know how to define and evaluate quality, relevance, reliability, and trust.
- Ownership in ambiguity. You take on complex problems, create clarity, and move teams forward without waiting for someone to hand you a fully formed specification.
- Exceptional product storytelling. You turn complex data and technical concepts into clear narratives that align teams and help senior leaders make decisions.
Preferred qualifications
- Track record of running experimentation programs at scale
- Shipped LLM or agentic features to production, including the evaluation frameworks behind them.
- Experience both building new products from scratch and scaling existing ones
- Experience with two-sided marketplaces, seller or merchant platforms, ads, or B2B growth
- Experience with recommendation systems or personalization
- Built tools for sales, account management or customer success teams
- Led products across multiple countries or markets
- Comfortable pulling and analyzing your own data
- Hands-on prototyping with AI tools
Benefits:
Benefits: Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much 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.
At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
The annual salary range for this position is $143,000.00 - $286,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock
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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, engineering, or related area and 9 years’ experience in product management. Option 2: 11 years’ experience in product management or related area.Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Master’s degree in Computer Science, Engineering, Business Administration, or related area and 8 years’ experience as a product manager, ideally working on consumer-facing, large-scale, highly complex B2B/C products, Supervisory experience, 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. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture. Masters: Business Administration, Masters: Computer Engineering, Masters: Computer SciencePrimary Location...
850 Cherry Ave, San Bruno, CA 94066-3031, United States of America 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. This policy applies to all employees and aims to create a safe and productive work environment.
Salary Context
This $143K-$286K range is above the median for AI/ML Engineer roles in our dataset (median: $176K across 1540 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Walmart, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,857 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. Disclosed range: $143K to $286K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Walmart AI Hiring
Walmart has 18 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist, AI Software Engineer, AI Product Manager. Positions span Sunnyvale, CA, US, San Bruno, CA, US, Bentonville, AR. Compensation range: $286K - $416K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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