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MLops Consultant

3 months ago

Bangalore Urban, India Capgemini Full time

Position: MLops

Location: PAN India


Job Summary:

We are searching for a highly skilled and experienced MLOps Consultant to join our growing team. In this role, you will play a pivotal role in ensuring the smooth transition of machine learning models from development to production. You will collaborate with data scientists, engineers, and business stakeholders to implement best practices for MLOps, optimize model performance, and ensure the ongoing success of our machine learning initiatives.


Responsibilities:

  • Partner with data scientists and engineers to understand the technical aspects of machine learning models.
  • Design and implement MLOps pipelines for training, deployment, monitoring, and serving of machine learning models.
  • Automate the machine learning lifecycle, including data versioning, model training, and deployment.
  • Select and implement appropriate tools and technologies for MLOps, such as version control systems, containerization technologies (Docker, Kubernetes), and monitoring tools (Prometheus, Grafana).
  • Develop and implement a comprehensive monitoring strategy for production ML models, including anomaly detection and performance metrics.
  • Collaborate with DevOps teams to ensure seamless integration of MLOps pipelines with existing CI/CD workflows.
  • Continuously improve MLOps processes to enhance efficiency, scalability, and reliability.
  • Stay up-to-date on the latest advancements in MLOps tools and methodologies.
  • Document MLOps processes and best practices.
  • Provide guidance and support to data science and engineering teams on MLOps best practices.
  • Participate in code reviews for MLOps pipelines.


Qualifications:

  • Master's degree in Computer Science, Data Science, or a related field (or equivalent experience).
  • 3+ years of experience in a technical role related to machine learning or data science.
  • Proven experience in designing and implementing MLOps pipelines.
  • Strong understanding of machine learning concepts and algorithms.
  • Experience with cloud platforms (AWS, Azure, GCP) is a plus.
  • Familiarity with version control systems (Git) and containerization technologies (Docker, Kubernetes).
  • Experience with MLOps tools (MLflow, Kubeflow, Metaflow) is a plus.
  • Experience with monitoring tools (Prometheus, Grafana) is a plus.
  • Excellent communication, collaboration, and problem-solving skills.
  • Ability to work independently and as part of a team.
  • Strong attention to detail and a commitment to quality.