Job Summary :

We are seeking a Principal Data Scientist to drive innovation within Walmart International Search and Personalization. This role will be instrumental in enhancing our entire Search Stack - including Pre-retrieval, Retrieval and Ranking along with recommendation systems, and user personalization strategies across the user journey by leveraging cutting-edge ML techniques. You will lead high-impact projects, collaborate with cross-functional teams, and shape the future of how customers discover and interact with our platform.

What you'll do:

• Develop and Optimize ML Models: Design and deploy machine learning models for search relevance, ranking, query understanding, embeddings, personalization, and recommendations.
• Lead Algorithmic Innovations: Drive the development of deep learning, reinforcement learning, multi-task learning, and LLM-based techniques to improve search and personalization performance.
• Lead Model Architecture Discussions: Define and drive end-to-end ML architecture decisions, ensuring models are scalable, efficient, and aligned with business needs. Collaborate with ML engineers and platform teams to design architectures that integrate seamlessly into production.
• Scale AI in Production: Work closely with MLOps and engineering teams to deploy and maintain scalable ML solutions that power real-time experiences.
• Experimentation and Evaluation: Define KPIs, design A/B tests, and lead offline/online evaluations to measure and optimize model effectiveness.
• Cross-functional Collaboration: Partner with Product, Engineering, UX, and Business teams to align machine learning initiatives with strategic goals.
• Mentor and Influence: Provide technical leadership, mentor junior team members, and contribute to the broader ML and AI strategy for the organization.

What you'll bring:

• Expertise in Search & Personalization: Strong experience in information retrieval, search ranking, query intent classification, and recommendation systems.
• Advanced ML & AI Knowledge: Proficiency in deep learning (Transformer models, embeddings, contrastive learning), NLP (LLMs, BERT, RAG-based systems), and graph-based personalization techniques.
• Applied Experience: Hands-on experience in deploying ML models at scale using frameworks like TensorFlow, or PyTorch
• Open-Source ML Technologies: Strong experience with distributed computing, feature stores (Feast), and ML platforms such as MLflow and Kubeflow.
• Strong Programming & Engineering Skills: Proficiency in Python, Scala, or Java, with experience in writing production-quality ML pipelines.
• Proven Track Record: Experience in designing and leading ML projects that drive measurable business impact.
• Problem-Solving & Innovation: Ability to tackle ambiguous problems and drive ML advancements in Search & Personalization.
• Excellent Communication: Ability to convey complex technical concepts to business stakeholders and executive leadership.