Machine Learning Specialist

1 month ago

Anantapur, India Promaynov Executive Trainers LLP Full time

Please find below job details :

Role : Senior Associate Manager – MLOps Engineer

Experience : 5 - 8 years


Location : Bangalore


Mode : WFO (5 days)

Employment mode : Contractual

Contract Period : 1 year

Job Description :

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.

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