MLOps Engineer

2 months ago


Bangalore, Karnataka, India Promaynaov Advisory Services Pvt Ltd Full time

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)
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