Staff, Data Scientist (Recommendation)

Experteer Overview In this role you will develop scalable ML solutions for personalised recommendations, collaborating with the Walmart Personalization team to improve customer experiences across platforms. You will translate product needs into AI problems, build production-grade models, and experiment with cutting-edge techniques to deliver measurable customer impact. You will operate in a fast-moving, cross-functional environment and contribute to scalable AI innovations such as LLMs and graph-based models. This is an onsite, Sunnyvale-based role with a strong emphasis on delivering impactful, customer-centric AI in retail. Compensation / Benefits * Map product and business requirements to ML/AI problems * Design and implement scalable ML models for recommender systems and other scalable models * Analyze large datasets to derive actionable insights * Build robust modelling systems using LLMs, deep learning, and advanced statistical methods * Collaborate cross-functionally to align with product goals * Experiment and iterate in fast development cycles * Focus on scalability, production-readiness, and impact on customer engagement Tasks * PhD with 2+ years or MS with 5+ years in a relevant field * Experience deploying production-grade ML models * Strong background in reinforcement learning and contextual bandits * Proficiency in Java, Python, PySpark * Experience with TensorFlow and PyTorch * Knowledge of dimensionality reduction, predictive modelling, clustering, and text mining * Ability to innovate and adapt to new technologies quickly * Preferred: experience in search/recommendation systems Key requirements * 401(k) match * stock purchase plan * paid maternity and parental leave * PTO including sick leave * health plans (medical, vision, dental) * Live Better U education benefit

with product goals * Experiment and iterate in fast development cycles * Focus on scalability, production-readiness, and impact on customer engagement Tasks * PhD with 2+ years or MS with 5+ years in a relevant field * Experience deploying production-grade ML models * Strong background in reinforcement learning and contextual bandits * Proficiency in Java, Python, PySpark * Experience with TensorFlow and PyTorch * Knowledge of dimensionality reduction, predictive modelling, clustering, and text mining * Ability to innovate and adapt to new technologies quickly * Preferred: experience in search/recommendation systems Key requirements * 401(k) match * stock purchase plan * paid maternity and parental leave * PTO including sick leave * health plans (medical, vision, dental) * Live Better U education benefit