About Store No8

We are the incubation arm of Walmart. Store No8 was formed in 2017 as part of Walmart’s larger innovation mission to shape the future of commerce. We pursue big ideas and take risks by stepping outside of Walmart’s core business to focus on leapfrog capabilities across conversational commerce, mixed reality, in-store digitization, and more. Our ultimate goal: fuel Walmart’s core business, create new operational efficiencies, and unlock amazing experiences for our customers in the long-term.

About the Role

As a Staff AI Engineer for one of our Store Nº8’s portfolio companies, you will focus on building AI/ML algorithms to create personalized shopping experience for our customers. You will partner with data engineer, data science, product, business, UX, engineering, and operations. You will need to be a self-starter with a bias for action and excellent communication skills.

This is a rare opportunity, moving at the speed of a start-up, with the backing and in house data (lots of data) of the Fortune 1 company. You will bridge the art of what’s possible across today’s rapidly evolving consumer & food landscape.

What You Will Do:

• Build prototype AI/ ML models and tools to help us understand our customers and create personalized customer recommendations across multiple use cases and productize solutions to scale
• Deeply understand customers, their behaviors and pain points, and develop a diversity of AI models addressing an array of customers’ needs
• Translate business needs into AI/ML problems and create innovative solutions to advance our business goals
• Determine the types and amount of data needed and work with data engineer to identify data sources and ingest into data lake
• Structure, standardize, and annotate data into processable formats for ML; enrich data with necessary attributes to allow sophisticated personalization
• Help shape the way our data science team does work - researching and making key decisions about what we build, how we build it, and which tools are best for solving our problems
• Work alongside software and data engineers to implement data processing and visualization systems that make data readily available and simplify how insights are communicated
• Evaluate the performance of AI models and make tradeoffs against quality metrics
• Investigate, and resolve performance issues in a timely manner

Preferred Qualifications

• Bachelor’s or Master’s degree in Mathematics, ML, statistics, Computer Science, Software/Data Engineering, or a related field
• Strong mathematical background in probability, statistics, and optimization algorithms.
• Experience in building machine learning models and deploying them to production to make real decisions, then measuring the impact of these decisions.
• Deep understanding of and have applied various machine learning techniques for solving real-world problems.
• Expertise with advanced programming skills in Python, Java or any of the major languages to build robust algorithms
• Proficient with SQL and can work “full stack” to integrate solutions with our data ecosystem
• Confident in taking ownership of projects from start to finish and enjoy the process of turning nebulous ideas into reality
• Excellent communication skills

• A self-starter who drives projects and builds strong relationships with stakeholders and teams to tackle large cross-functional efforts

• Thrive with minimal guidance and process

• Worked in both small teams/incubators and large corporations

Perks and Benefits

Beyond competitive pay, 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.

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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 diversity- unique styles, experiences, identities, ideas, and opinions – while being inclusive of all people.