Machine Learning Engineer-OPs

5 - 10 years

0 Lacs

Posted:3 weeks ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

As a hiring partner for many IT organizations,We are hiring for below position as direct full time on the payroll as a permanent employee of the Hiring Organization.
Please share your updated word format resume with CTC, Location and Notice period at "info@unimorphtech.com"

Role : Machine Learning Operations Engineer

## Key Skills :

ML Solutions,MLOPs,Machine Learning model deployment, monitoring & governance,Design and develop machine learning pipelines and frameworks,Azure,Snowflake,Machine learning pipeline,framework,Machiice Learning Engineering,data science,Python,TensorFlow, PyTorch,Data modeling,cloud aechitecture.

# Roles and Responsibilities

  • Work with stakeholders to define machine learning solution design (based on cloud services like Azure and Snowflake), that adheres to industry best practices.
  • Design and develop machine learning pipelines and frameworks to support enterprise analytical/reporting needs.
  • Provide guidance and collaborate on model deployment design with data science, ML engineering, and data quality teams.
  • Manage and configure the cloud environments and related ML services.
  • Implement improvements and new tools and approaches aimed at model integration, storage, profiling, processing, management and archival.
  • Recommend improvements and platform development to meet strategic objectives of Global Technology and the MPG business.
  • Utilize Agile practices to manage and deliver features.
  • Must stay current with key technologies and practices so that both current and new needs can be assessed for suitability to business requirements.

# Experience :

  • Bachelor's degree in Computer Science, Engineering or Technical Field preferred.
  • Minimum 3-5 years of relevant experience.
  • Proven experience in machine learning engineering and operations.
  • Profound understanding of machine learning concepts, model lifecycle management, and experience in model management capabilities including model definitions, performance management and integration.
  • Execution of model deployment, monitoring, profiling, governance and analysis initiatives.
  • Excellent interpersonal, oral, and written communication; Ability to relate ideas and concepts to others; write reports, business correspondence, project plans and procedure documents.
  • Solid Python, ML frameworks (e.g., TensorFlow, PyTorch), data modeling, and programming skills.
  • Experience and strong understanding of cloud architecture and design (AWS, Azure, GCP).
  • Experience using modern approaches to automating machine learning pipelines.
  • Agile and Waterfall methodologies.
  • Ability to work independently and manage multiple task assignments within a structured implementation methodology.
  • Personally invested in continuous improvement and innovation.
  • Motivated, self-directed individual that works well with minimal supervision.
  • Must have experience working across multiple teams/technologies.

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