MLOps Engineer

Capgemini

Bengaluru

On-site

INR 1,500,000 - 2,200,000

Full time

14 days+

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Job summary

Capgemini in Bengaluru is seeking an experienced MLOps Engineer to design, implement, and maintain end-to-end ML pipelines for training, evaluation, and deployment. You will collaborate with data scientists and software engineers to operationalize models and serve frameworks, while building robust CI/CD for ML workflows.

The role emphasizes containerization with Docker and orchestration via Kubernetes, plus model/data versioning and cloud experience on AWS.

Qualifications

  • Experience building end-to-end ML pipelines and deploying models.
  • Experience with MLOps tools and serving frameworks.
  • Strong Python programming and testing practices.

Responsibilities

  • Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment.
  • Collaborate with data scientists and software engineers to operationalize ML models.
  • Develop and maintain CI/CD pipelines for ML workflows.
  • Implement monitoring and logging solutions for ML models.
  • Optimize ML infrastructure for performance, scalability, and cost-efficiency.

Skills

Python
ML frameworks
CI/CD
Cloud AWS

Tools

Docker
Kubernetes
TensorFlow Serving
TorchServe
Model versioning
Data versioning

Job description

Job Description

MLOps


  • Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment.
  • Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools.
  • Develop and maintain CI/CD pipelines for ML workflows
  • Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe)
  • Optimize ML infrastructure for performance, scalability, and cost-efficiency
  • Strong programming skills in Python with experience in ML frameworks; understanding of ML-specific testing and validation techniques
  • Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques
  • Proficiency in cloud platform (AWS, Azure,)
Job Classification

Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data Science & Machine Learning - OtherEmployement Type: Full time

Contact Details:

Company: CapgeminiLocation(s): Bengaluru Ability to work in a team environment with members of varying skill levels. Highly motivated. Learns quickly.

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