Talent.com
MLOps Engineer

MLOps Engineer

Wenger and WatsonBangalore
18 days ago
Job description

Description :

  • Experience : 5 - 10 yrs.
  • Locations : Bangalore, Chennai, Mumbai, Pune, Hyderabad.

Key Responsibilities :

  • Design, develop, and deploy machine learning models using AWS SageMaker for various business applications.
  • Implement end-to-end ML pipelines from data preprocessing to model serving and monitoring.
  • Build and maintain automated model training, validation, and deployment workflows.
  • Optimize model performance, scalability, and cost-effectiveness in production environments.
  • Create interactive ML applications and demos using Gradio for stakeholder demonstrations and user interfaces.
  • Develop robust Python applications for data processing, feature engineering, and model inference.
  • Build APIs and microservices for model serving and integration with existing systems.
  • Implement model versioning, A / B testing frameworks, and continuous integration / deployment practices.
  • ML infrastructure on AWS, including SageMaker endpoints, batch transform jobs, and processing jobs.
  • Monitor model performance, data drift, and system health in production environments.
  • Collaborate with DevOps teams to ensure reliable and scalable ML operations.
  • Implement security best practices for ML systems and data handling.

    • Technical Skills :

  • Expert-level proficiency in Python programming with strong software development practices.
  • Extensive hands-on experience with AWS SageMaker, including training jobs, endpoints, and pipelines.
  • Proven experience with Gradio for building ML application interfaces.
  • Strong background in machine learning algorithms, statistical modeling, and deep learning frameworks (PyTorch, TensorFlow, scikit-learn).
  • Experience with MLOps practices, model versioning, and deployment strategies.
  • Deep understanding of AWS ecosystem (EC2, S3, Lambda, IAM, CloudFormation).
  • Experience with containerization technologies (Docker, Kubernetes).
  • Knowledge of data engineering tools and workflows (Apache Spark, Airflow, or similar).
  • Familiarity with infrastructure as code and CI / CD pipelines.
  • Strong experience with version control systems (Git), code review processes, and agile development.
  • Excellent problem-solving skills and ability to debug complex distributed systems.
  • Experience with data visualization tools and techniques.
  • Strong communication skills for presenting technical concepts to diverse audiences.

    • (ref : hirist.tech)

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    Mlops Engineer • Bangalore