MLops - 4+ years - Gurgaon
| Location: | Gurgaon |
| Functional Practices: | Data Science/Machine Learning, Analytics , Devops/Site Reliability Engineer, Technology |
| Job type: | Permanent |
| Contact name: | Aayushi Grover |
| Contact email: | aayushi.grover@crescendogroup.in |
| Job ref: | 40223 |
| Published: | over 1 year ago |
| Startdate: | 13 April 2024 - 13 April 2024 |
MLops - 4+ years - Gurgaon
An exciting opportunity for the one having at least 3 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: Gurgaon
Your future employer: A leading general insurance player, headquartered in London and building a global capability center in Gurgaon, India.
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 aayushi.grover@crescendogroup.in
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