Staff Data Scientist — Recommender & RL (Sunnyvale Onsite)

Walmart; Sunnyvale (CA); On-site; USD 143,000 - 286,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Stock purchase plan

Paid time off

Job summary

Walmart Global Tech in Sunnyvale, CA is seeking an applied scientist to build scalable recommender systems and ML solutions for marketplace goals. You will work on LLMs, reinforcement learning, and AI models in a fast-moving, cross-functional setting.

The role emphasizes production-grade modelling, data analysis, and collaboration with engineering, data science, and product teams. On-site only; visa sponsorship is not available.

Qualifications

• PhD with 2+ years or MS with 5+ years of industry/academic experience in ML/CS/OR.
• Experience implementing and scaling production-grade modelling systems.
• Strong background in reinforcement learning and contextual bandits.

Responsibilities

• Map product and business requirements to ML/AI problems and solve them.
• Research, design and implement scalable ML models for recommender systems.
• Perform data analysis and modeling on large datasets for insights.
• Build robust modelling systems using LLMs, deep learning and advanced statistics.
• Collaborate across teams in a fast-moving environment.

Skills

Recommender systems

Information retrieval

Reinforcement learning

Java

Python

PySpark

TensorFlow

PyTorch

Dimensionality reduction

Predictive modelling

Clustering

Text mining

Education

PhD in Computer Science / Machine Learning / Statistics or related field

MS in Computer Science / Machine Learning / Operations Research or related field

Tools

TensorFlow

PyTorch

Java

Python

PySpark

Job description

Walmart Global Tech in Sunnyvale, CA is seeking an applied scientist to build scalable recommender systems and ML solutions for marketplace goals. You will work on LLMs, reinforcement learning, and AI models in a fast-moving, cross-functional setting.

The role emphasizes production-grade modelling, data analysis, and collaboration with engineering, data science, and product teams. On-site only; visa sponsorship is not available.