Data Scientists – Remote / Telecommute at Cynet Systems #vacancy #remote

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.