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MLOps Engineer @ Capgemini

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Capgemini  MLOps Engineer

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 & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Science & Machine Learning - Other
Employement Type: Full time

Contact Details:

Company: Capgemini
Location(s): Bengaluru

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Keyskills:   MLOps Machine Learning Python Ci Cd Pipeline Artificial Intelligence Aws Sagemaker Ml Pipelines AWS

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Capgemini

Capgemini Engineering combines, under one brand, a unique set of strengths from across the Capgemini Group: the world leading engineering and R&D services of Altran acquired by Capgemini in 2020 - and Capgemini's digital manufacturing expertise. With broad industry knowledge and cutting-edge ...