Job Description:
Responsibilities:
- Work with Walmart’s AI/Client Platform Enablement team within the eCommerce Analytics team.
- The broader team is currently on a transformation path, and this role will be instrumental in enabling the broader team’s vision.
- Work closely with other Data Scientists to help with production models and maintain them in production.
- Deploy and configure Kubernetes components for production cluster, including API Gateway, Ingress, Model Serving, Logging, Monitoring, Cron Jobs, etc.
- Improve the model deployment process for MLE for faster builds and simplified workflows.
- Be a technical leader on various projects across platforms and a hands-on contributor of the entire platform’s architecture.
- Responsible for leading operational excellence initiatives in the AI/Client space which includes efficient use of resources, identifying optimization opportunities, forecasting capacity, etc.
- Design and implement different flavors of architecture to deliver better system performance and resiliency.
- Develop capability requirements and transition plan for the next generation of AI/Client enablement technology, tools, and processes to enable Walmart to efficiently improve performance with scale.
Skills:
- bility to transform designs ground up and lead innovation in system design.
- Deep understanding of GenAI applications and NLP field.
- Hands on experience in the design and development of NLP models.
- Experience in building LLM-based applications.
- Design and development of MLOps pipelines.
- Fundamental understanding on the data science parameterized and non-parameterized algorithms.
- Knowledge on AI/Client application lifecycles and workflows.
- Experience in the design and development of an Client pipeline using containerized components.
- Have worked on at least one Kubernetes cloud offering (EKS/GKE/AKS) or on-prem Kubernetes (native Kubernetes, Gravity, MetalK8s).
- Programming experience in Python, Pyspark, Pytorch, Langchain, Docker, Kubeflow.
- bility to use observability tools (Client, Prometheus, and Grafana ) to look at logs and metrics to diagnose issues within the system.
- Experience with Web development.
Education and Experience:
- 6+ years relevant experience in roles with responsibility over data platforms and data operations dealing with large volumes of data in cloud based distributed computing environments.
- Graduate degree preferred in a quantitative discipline (e.g., computer engineering, computer science, economics, math, operations research).
- Proven ability to solve enterprise level data operations problems at scale which require cross-functional collaboration for solution development, implementation, and adoption.
Notes:
- We are looking for a data scientist who can contribute to the following domains.
- Design and development of GenAI applications Deeper understanding of the NLP field.
- Hands on experience in the design and development of NLP models Experience in building LLM-based applications.
- Design and development of MLOps pipelines Fundamental understanding on the data science parameterized and non-parameterized algorithms.
- Knowledge on AI/Client application lifecycles and workflows.
- Experience in the design and development of an Client pipeline using containerized components.
PySpark MLOps Prometheus Natural language processing (NLP) kubeflow Docker Data Science Python Web Developer Grafana PyTorch client