MLOps Engineer - Python Programming

Role : MLOps Exp : 5 years Location : Bangalore Working days : 5 days Mode of employment : Contract (1 year - after a year it will be extended) Role & Responsibilities : - Deploy and maintain machine learning models, pipelines, and workflows in production environment. - Re-package (deployment process) ML models that have been developed in the non-production ML environment by ML Teams for deployment to the production ML environment. - Perform the required MLOps engineering development to refactor the non-production ML model implementation to an "ML as Code" implementation. - Create, manage, and execute ServiceNow change requests in accordance with the IT Change Management process to manage the deployment of new models. - Build and maintain machine learning infrastructure that is scalable, reliable, and efficient. - Collaborate with data scientists and software engineers to design and implement machine learning workflows. - Implement monitoring and logging tools to ensure that machine learning models are performing optimally. - Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems. - Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc. - Support model development, with an emphasis on auditability, versioning, and data security. - Create and maintain technical documentation for machine learning infrastructure and workflows. - Stay up to date with the latest developments in machine learning and cloud computing technologies. - Provide expert data PaaS on Azure storage; big data platform services; server-less architectures; Azure SQL DB; NoSQL databases and secure, automated data pipelines. - Work collaboratively and use sound judgment in developing robust solutions while seeking guidance on complex problems. Basic Qualifications (Must have) : - Bachelor's or master's degree in computer science, engineering or related field. - 5 years of experience in software development, machine learning engineering or related field. - Strong understanding of machine learning concepts and frameworks. - Hand-on experience in Python. - Familiarity with DevOps practices and tools such as Kubernetes, Docker, Jenkins, Git. - Experience in developing and deploying machine learning models in a production environment. - Experience working with cloud computing and database systems. - Experience building custom integrations between cloud-based systems using APIs. - Experience developing and maintaining ML systems built with open-source tools. - Experience developing with containers and Kubernetes in cloud computing environments. - Ability to translate business needs to technical requirements. - At least 2 years of data pipeline and data product design, development, delivery experience and deploying ETL/ELT solutions on Azure Data Factory. - Strong analytical and problem-solving skills. Good to Have Skills : - Cloud migration methodologies and processes including tools like Azure Data Factory, Event Hub, etc. - Experience in using Hadoop File Formats and compression techniques. - DevOps on an Azure platform. - Experience working with Developer tools such as Visual Studio, GitLab's, Jenkins, etc. - Experience with private and public cloud architectures, pros/cons, and migration considerations. - Proven ability to work independently. - Proven ability to work in a team-oriented environment and work collaboratively in a problem-solving environment. - Experience with MLOps in Azure preferred. - Azure native data/big-data tools, technologies and services experience including - Storage BLOBS, ADLS, Azure SQL DB, and SQL Data Warehouse. - Excellent written and oral communication and interpersonal skills. - Excellent organizational and multi-tasking. Great-to-Have Skills : - Azure MCSA Cloud Platform Training & Certification - MCSD Azure Solutions Architect Training & Certification - Multi-cloud experience is a plus. (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 11/26/2024