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MLOPS Remote (India)

Role overview

Qualifications

  • Minimum 2 years in a relevant field
  • Proven experience in deploying machine learning models effectively in production environments.
  • Proficiency in automation and orchestration tools for managing ML workflows.
  • Strong understanding and implementation of model monitoring solutions for real-time performance tracking.

Responsibilities

  • Deploy machine learning models into production environments efficiently and effectively.
  • Utilize automation and orchestration tools to manage and streamline ML workflows.
  • Implement monitoring solutions to track model performance real-time and ensure optimal functionality.
  • Enforce scalability in machine learning systems to handle diverse and fluctuating workloads reliably.

Key facts

Hard skills

Other skills

  • Collaboration

About the company

Insignia Consultancy Solutions logo

Insignia Consultancy Solutions

Insignia is the leading global workforce solutions and services company. In today's fast-changing world of work, we help organizations transform by sourcing, assessing, developing and managing the talent that enables them to win, while connecting millions of individuals to meaningful, sustainable employment that enables them to thrive.

Company details

Company size11 - 50

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Job description

Job Brief:

## Job Description: MLOps Engineer

**Position:** MLOps Engineer  
**Experience:** Minimum 2 years in a relevant field

### Responsibilities:
- Deploy machine learning models into production environments efficiently and effectively.
- Utilize automation and orchestration tools to manage and streamline ML workflows.
- Implement monitoring solutions to track model performance real-time and ensure optimal functionality.
- Enforce scalability in machine learning systems to handle diverse and fluctuating workloads reliably.
- Collaborate closely with data scientists, developers, and operations teams for a seamless integration of ML solutions.
- Contribute to the optimization, maintenance, and enhancement of ML operations and processes.

### Requirements:
- Proven experience in deploying machine learning models effectively in production environments.
- Proficiency in automation and orchestration tools for managing ML workflows.
- Strong understanding and implementation of model monitoring solutions for real-time performance tracking.
- Ability to ensure scalability of machine learning systems to handle varying workloads efficiently.
- Excellent collaboration skills to work with cross-functional teams effectively.

If you meet the above requirements and are passionate about the intersection of machine learning and operations, we encourage you to apply and be a key part of our dynamic team.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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