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Category: Technology
Location:
About our client:
Our client is a global technology company specializing in platform-based digital transformation, supporting businesses to become connected, open, intelligent and scalable. Our client's methodology brings together industry expertise, platform technology excellence, design innovation and strategic engagement models to deliver sustained value to customers.
They are a trusted partner of world leaders in the retail, manufacturing, distribution, travel, services and software industries, their software portfolio includes Retail Platform, Modern Distribution, Digital Travel, E-commerce, enterprise development automation, Commodity Trading and Risk Management and AI Powered Customer Experience (CX). Our client services are built on Microsoft Dynamics 365, Microsoft Azure, AWS, Cloud Engineering and Managed Services delivery promise.
As world leaders in digital technologies including IoT, Artificial Intelligence, Machine Learning, Robotic Process Automation, Chatbots, Block Chain and Cyber Security, their people and systems are nurtured to deliver on our commitment to excellence in business technology solutions.
Requirements
MLOps Engineer | Remote
10+ years of IT experience in which at least 6+ years of relevantexperience primarily in MLOps, Cloud, Dockerization & Containerization.
Develop best practices and how-to guides for MLOps practicesrelating Git, CI/CD, Input data unit and statistical testing, Experimenttracking, Model Registry, Scheduling of ML pipelines, Production driftmonitoring and alerting, Optimization of cloud compute resources
Adopt best practices for writing processed data (ML features) toappropriate data lakes, warehouses, or feature stores Extensive experience with infrastructure provisioning and configuringpublic and hybrid clouds with mandatory GCP experience.
Dockerization of Machine Learning scripts and deployment in Google CloudPlatform.
Ability to create automatically and deploy Machine Learning notebooks.Also, ability to establish connection with Big Data infrastructure from theMachine Learning notebooks.
Experience administering Kubernetes, Google Kubernetes Engine (GKE) andunderstanding of manifest management with Helm.
Experience with CI/CD pipelines and related tools such as Jenkins orCircleCI and Google Cloud Build.
Experience with configuration management tools and deployment tools likeTerraform and Google Deployment Manager.
Good knowledge of other tools likePuppet, Ansible, Chef, Consul, Packer etc.
Setup of Monitoring and Alerts for Production workloads in Google CloudPlatform.
Experience in automating multiple systems using Bash and languages suchas Python and Go.
Recommend and implement automated solutions that will improve theperformance and reliability of the system.
Strong understanding and experience operating in an agile developmentenvironment.
Strong communication skills across the board, with a passion for findingand sharing best practices and driving greater discipline.
Excellent verbal and written communication skills in English.
Nice to have:
Experience in managing Linux/Unix platforms, application serveradministration (Tomcat, JBoss, etc.) and DNS, Linux system configuration andadministration (CentOS, RedHat, etc.).
Good exposure with monitoring tools geared towards user experience anddeep diagnostics (Splunk, New Relic, AppDynamics, Prometheus, Grafana, etc.) Details Originally posted on Himalayas