MLOPS Engineer- Docker (6 -9 years)

Location: India
Discipline: Technology
Job type: Permanent
Contact name: Gurpreet Kaur

Contact email: gurpreet.kaur@crescendogroup.in
Job ref: 36489
Published: 5 days ago
Startdate: 17/03/2022

MLOPS Engineer- Docker (6 - 9 years)

 

An exciting opportunity for the one having overall 6 - 9 years of experience out of which atleast 4 years of  experience working with ML services and DevOps concepts, and practices. The candidate must be having experience working in cross-functional Agile engineering teams and familiarity with standard concepts and technologies used in CI/CD build, deployment pipelines. A perfect role fit for the one having good hands on experience in Designing, building and optimize applications’ containerization and orchestration with Docker.

 

Location: Bangalore/Mumbai/ Gurgaon

 

Your future employer: One of the most prominent players in the Artificial Intelligence space providing services in Consumer-packaged goods, insurance, Retail& Technology etc.

Responsibilities:

  • Operating and maintaining systems supporting the provisioning of new clients, applications, and features.

  • Day-to-day monitoring of the production service delivery environment to ensure all services and applications are operating optimally and SLAs are met.

  • Handling/managing E2E ML lifecycle.

  • Building E2E ML pipeline/accelerators for either batch or real-time predictions.

 

 

Requirements:

  • At least 3 years’ experience working with ML services and DevOps concepts, and practices.

  • Experience working in cross-functional Agile engineering teams.

  • Familiarity with standard concepts and technologies used in CI/CD build, deployment pipelines.

  • Model management and model performance monitoring (drift monitoring).

  • Git for Source code management.

  • Knowledge of machine learning frameworks (either of): Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, Scikit-Learn.

  • Hands-on Python 3.x, Pandas, NumPy, SQL

  • Should have hands-on in below technologies:

    • Model Repository (either of): MLFlow, Kubeflow Model Registry

    • Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, or any relevant ML E2E PaaS/SaaS.

  • Hands-on with REST API for real-time and near real-time (streaming) servings.

 

What is in it for you?

  • Work in diverse culture and global team

  • Grow in culture focused on training and mentoring

  • Work in a fast-paced environment in an established brand

Reach Us:

If you think you are perfect fit for this role, kindly drop me an email along with your updated CV at gurpreet.kaur@crescendogroup.in