(usa) Staff, Data Scientist

Walmart Walmart · Retail · Sunnyvale, CA +1

Staff Data Scientist role focused on building and deploying ML systems for translation, localization, contextualization, and personalization within Walmart's global tech division. The role involves applied research in NLP and multilingual AI, building scalable data pipelines, and end-to-end ownership of ML systems. Experience with sequence-to-sequence modeling, Transformers, LLMs, and ML frameworks like PyTorch or TensorFlow is required.

What you'd actually do

  1. Lead the design, development, and evaluation of machine learning systems for translation, localization, contextualization and personalization.
  2. Drive applied research in NLP and multilingual AI, with opportunities to publish or patent your work.
  3. Build scalable data pipelines for real-time and batch multilingual experience use-cases, ensuring robustness, performance, and data quality.
  4. Partner with product and business stakeholders to understand business needs, define technical roadmaps, and own the end-to-end lifecycle of data-driven solutions from ideation to deployment.

Skills

Required

  • MS or PhD in Computer Science, Machine Learning, or a related technical field.
  • Experience with sequence-to-sequence modeling using Transformers or LLMs.
  • Proficiency with machine learning frameworks such as PyTorch or TensorFlow.
  • Fluency in English and at least one other language.
  • End-to-end ownership of ML systems, from research and prototyping to experimentation and deployment

Nice to have

  • French strongly preferred.
  • Python
  • Spark
  • Scala
  • R
  • scikit learn
  • tensorflow
  • torch
  • creating inclusive digital experiences
  • implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards
  • assistive technologies
  • integrating digital accessibility seamlessly
  • accessibility best practices
  • Walmart’s accessibility standards and guidelines for supporting an inclusive culture

What the JD emphasized

  • end-to-end ownership of ML systems
  • proven track record of building and deploying accurate, impactful, and efficient ML systems

Other signals

  • applying cutting-edge machine learning to solve real-world challenges at massive scale
  • multilingual experiences drive multi-million-dollar growth
  • lead the design, development, and evaluation of machine learning systems for translation, localization, contextualization and personalization
  • Drive applied research in NLP and multilingual AI
  • Build scalable data pipelines for real-time and batch multilingual experience use-cases
  • end-to-end ownership of ML systems, from research and prototyping to experimentation and deployment