MLOps Lead Engineer

IT solutions specialized in Apps Lifecycle management. (MG1)

MLOps Lead Engineer

MLOps Lead Engineer at IT solutions specialized in Apps Lifecycle management. (MG1) · Bengaluru (Bangalore) · 5 - 6 years · ₹10L - ₹12L / yr · Posted 16 Jun 2021

MLOps Lead Engineer

at IT solutions specialized in Apps Lifecycle management. (MG1)

Agency job

via Multi Recruit

5 - 6 yrs

₹10L - ₹12L / yr

Bengaluru (Bangalore)

Skills

Mlops

Kubernetes

Docker

Ansible

PySpark

Jenkins

Python

MLOps Workflow Automation

Automate and maintain ML and Data pipelines at scale
Collaborate with Data Scientists and Data Engineers on feature development teams to containerize and build out deployment pipelines for new modules
Maintain and expand our on-prem deployments with spark clusters
Design, build and optimize applications containerization and orchestration with Docker and Kubernetes and AWS or Azure

Skills:

5 years of IT experience in data-driven or AI technology products
Understanding of ML Model Deployment and Lifecycle
Extensive experience in Apache airflow for MLOps workflow automation
Experience is building and automating data pipelines
Experience in working on Spark Cluster architecture
Extensive experience with Unix/Linux environments
Experience with standard concepts and technologies used in CI/CD build, deployment pipelines using Jenkins
Strong experience in Python and PySpark and building required automation (using standard technologies such as Docker, Jenkins, and Ansible).
Experience with Kubernetes or Docker Swarm
Working technical knowledge of current systems software, protocols, and standards, including firewalls, Active Directory, etc.
Basic knowledge of Multi-tier architectures: load balancers, caching, web servers, application servers, and databases.
Experience with various virtualization technologies and multi-tenant, private and hybrid cloud environments.
Hands-on software and hardware troubleshooting experience.
Experience documenting and maintaining configuration and process information.
Basic Knowledge of machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch

Automate and maintain ML and Data pipelines at scale
Collaborate with Data Scientists and Data Engineers on feature development teams to containerize and build out deployment pipelines for new modules
Maintain and expand our on-prem deployments with spark clusters
Design, build and optimize applications containerization and orchestration with Docker and Kubernetes and AWS or Azure

Skills:

5 years of IT experience in data-driven or AI technology products
Understanding of ML Model Deployment and Lifecycle
Extensive experience in Apache airflow for MLOps workflow automation
Experience is building and automating data pipelines
Experience in working on Spark Cluster architecture
Extensive experience with Unix/Linux environments
Experience with standard concepts and technologies used in CI/CD build, deployment pipelines using Jenkins
Strong experience in Python and PySpark and building required automation (using standard technologies such as Docker, Jenkins, and Ansible).
Experience with Kubernetes or Docker Swarm
Working technical knowledge of current systems software, protocols, and standards, including firewalls, Active Directory, etc.
Basic knowledge of Multi-tier architectures: load balancers, caching, web servers, application servers, and databases.
Experience with various virtualization technologies and multi-tenant, private and hybrid cloud environments.
Hands-on software and hardware troubleshooting experience.
Experience documenting and maintaining configuration and process information.
Basic Knowledge of machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch

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