Senior MLOps Engineer

4 weeks ago

Bengaluru, Karnataka, India Promaynov Full time
Job Title: Senior MLOps Engineer

Promaynov is seeking a highly skilled Senior MLOps Engineer to join our team. As a Senior MLOps Engineer, you will be responsible for designing, implementing, and maintaining machine learning infrastructure pipelines and workflows.

Key Responsibilities:

  • Deploy and maintain machine learning models, pipelines, and workflows in production environments.
  • Repackage ML models for deployment to production environments.
  • Perform MLOps engineering development to refactor non-production ML model implementations.
  • Create, manage, and execute ServiceNow change requests.
  • Build and maintain scalable, reliable, and efficient machine learning infrastructure.
  • Collaborate with data scientists and software engineers to design and implement machine learning workflows.
  • Implement monitoring and logging tools to ensure optimal machine learning model performance.
  • Identify and evaluate new technologies to improve performance, maintainability, and reliability of machine learning systems.
  • Apply software engineering rigor and best practices to machine learning, including CI/CD automation.
  • Support model development with emphasis on auditability, versioning, and data security.
  • Create and maintain technical documentation for machine learning infrastructure and workflows.

Requirements:

  • 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.
  • Hands-on experience in Python.
  • Familiarity with DevOps practices and tools, such as Kubernetes, Docker, Jenkins, and Git.
  • Experience in developing and deploying machine learning models in production environments.
  • 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.

Preferred Qualifications:

  • Cloud migration methodologies and processes, including tools like Azure Data Factory and Event Hub.
  • Experience in using Hadoop File Formats and compression techniques.
  • DevOps on an Azure platform.
  • Experience working with developer tools, such as Visual Studio, GitLabs, and Jenkins.
  • 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 collaborate 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 multitasking skills.

Additional Information:

  • Azure MCSA Cloud Platform Training & Certification.
  • MCSD Azure Solutions Architect Training & Certification.
  • Multicloud experience is a plus.

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