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MLOps Engineer - Inperson Interview

CogniSoft TechnologiesConcord, CA🇺🇸United StatesPosted 14 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Responsibilities:
  • Deploy and maintain machine learning models in development and production environments.
  • Build and maintain CI/CD pipelines for ML applications.
  • Work with Git, Docker, Kubernetes, and cloud platforms such as AWS/Azure/Google Cloud Platform.
  • Automate model training, testing, deployment, and monitoring workflows.
  • Monitor model performance, application logs, and infrastructure.
  • Manage ML pipelines and datasets.
  • Collaborate with data scientists, ML engineers, and software developers.
  • Troubleshoot deployment and infrastructure issues.
  • Follow best practices for version control, security, and reproducible ML workflows.
Basic Skills Required:
  • Python and Linux fundamentals.
  • Git/GitHub.
  • Docker basics.
  • CI/CD concepts (Jenkins, GitHub Actions, GitLab CI, etc.).
  • Basic Kubernetes knowledge.
  • Basic cloud knowledge (AWS/Azure/Google Cloud Platform).
  • Understanding of ML lifecycle: data → training → validation → deployment → monitoring.
  • Basic knowledge of tools such as MLflow, Airflow, or Kubeflow is a plus.
 

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