Distinguished Data Scientist: Associate AI Experience

Walmart Walmart · Retail · Bentonville, AR +2

Distinguished Data Scientist to provide technical leadership and long-term vision for next-generation AI systems and platforms, focusing on building and deploying production ML systems and autonomous AI agents at scale. The role involves architecting large-scale AI systems, including conversational assistants and predictive agents with tool-calling, using frameworks like LangChain and RAG patterns. It also includes deploying NLP pipelines, designing agentic evaluation frameworks, and mentoring senior talent.

What you'd actually do

  1. Build and deploy production ML systems end-to-end: data pipelines, feature stores, model training, serving layers, monitoring, and feedback loops at scale
  2. Provide technical visionand lead advanced development in agentic AI, reinforcement learning, and simulation.
  3. Architect and deploy large-scale AI systems and autonomous AI agents — conversational assistants, predictive agents with tool-calling, and multi-agent orchestration systems using LangChain, Pydantic AI, and RAG patterns
  4. Design agentic evaluation frameworks that benchmark agent performance across task completion, code quality, and multi-step reasoning accuracy
  5. Deploy NLP pipelines at enterprise scale — semantic similarity across millions of records using BERT/SBERT embeddings and vector search (FAISS)

Skills

Required

  • Deep expertise in ML algorithms (XGBoost, CatBoost, LightGBM, Random Forest, AutoML) and deep learning (PyTorch, transformer architectures).
  • Production experience with NLP (BERT, SBERT, FAISS, RAG), computer vision (YOLO, CLIP), and time series forecasting (ARIMA, Prophet).
  • Hands-on experience building and orchestrating multiple AI agents with LangChain, RAG, tool integration, and memory management.
  • Multi-cloud ML platform proficiency — AWS SageMaker AND GCP (Vertex AI, BigQuery, BigQuery ML).
  • Strong Python skills (Pandas, NumPy, Scikit-learn) with containerization (Docker) and MLOps practices.
  • Advanced statistical analysis, experiment design, and causal inference
  • Experience deploying production-grade AI systems at scale.

Nice to have

  • PhD in AI, Machine Learning, Computer Science, Information Technology, Statistics, Applied Mathematics, Econometrics, or related field with relevant industry experience.

What the JD emphasized

  • architect end-to-end ML/AI systems
  • built and shipped multiple autonomous AI agents
  • Level 5+ on Steve Yegge’s Vibe Coding scale and can ship production systems through AI-assisted development
  • production ML systems end-to-end
  • large-scale AI systems and autonomous AI agents
  • agentic evaluation frameworks
  • Deploy NLP pipelines at enterprise scale
  • Experience deploying production-grade AI systems at scale

Other signals

  • Build and deploy production ML systems end-to-end
  • Architect and deploy large-scale AI systems and autonomous AI agents
  • Deploy NLP pipelines at enterprise scale
  • Experience deploying production-grade AI systems at scale