Machine Learning Engineer - MLOps

Company: DEEGIT, INC.
Location: Dallas, Texas, United States
Type: Full-time
Posted: 10.JUN.2021

Summary

Hi There, Hope you're doing great, This is Nanda from Deegit Inc. I have an excellent job opportunity with one of our premier clients. Si...

Description

Hi There,

Hope you're doing great,

This is Nanda from Deegit Inc. I have an excellent job opportunity with one of our premier clients.

Since it is an urgent business requirement your prompt response is appreciated.

You can reach me at or

Title : MLOps Consultant
Location : REMOTE

  • As a MLOps engineer, you will work on AI/ML solutions, defining and implementing a tool chain to enable our internal team an efficient operation such as MLOps, containerization (Docker, Kubernetes) for a project critical to our customer needs
  • Build and maintain tools and infrastructure for efficient software and AI/ML development
  • Use MLflow tool to -

o build and automate AI/ML workstream from data analysis, experimentation, operationalization, model training, model tuning to visualization

o Increase our deployment speed, including the process for deploying models and data pipelines into production

o manage on-prem deployments where compute is not on our cloud, but on customers' devices/private cloud

  • Improve and maintain CI/CD pipelines and do manual deployments incase needed
  • Build and maintain infrastructure as code in the cloud, that can scale when needed.
  • Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation).
  • Other responsibilities include documentation, hardware acquisition and regulatory compliance

Idea candidate would have

  • An experience of 3-4 years as DevOps or Cloud Engineer and atleast 1 year experience on automated deployment of ML models in production
  • A B. Tech degree in CSE from a top engineering college

Skills:

  • In-depth knowledge and experience using MLFlow or equivalent MLOps platform to manage complete ML lifecycle
  • Hands-on experience with either of cloud services - AWS/Azure/Google Cloud Platform.
  • Strong experience in scripting (Python, R, Scala)
  • Experience with TensorFlow, Pytorch or other deep learning frameworks, regression techniques, and anomaly detection.
  • Experience with DevOps/automation tools such as GitLab, Ansible, Docker, Kubernetes, Jenkins
  • Working knowledge of Multi-tier architectures: load balancers, caching, web servers, application servers and databases.
  • Hands-on software and hardware troubleshooting experience.
  • Experience documenting and maintaining configuration and process information.
- provided by Dice

 
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