Description

Job Description:

  • Manage the entire lifecycle of ML models, from development to deployment and maintenance.
  • Develop ML models in Python, using object-oriented programming in a modular manner.
  • Utilize AWS SageMaker for building, deploying, and managing ML pipelines.
  • Handle model versioning and lifecycle management using DVC and Git.
  • Implement scalable and modular solutions with Docker and serverless architectures (e.g., AWS Lambda).
  • Design and implement event-driven architectures, including triggers and event sources, to automate and streamline ML workflows.
  • Create and manage feature stores to enhance model reuse and efficiency.
  • Design and maintain CI/CD pipelines for robust ML model deployment.
  • Evaluate model performance using relevant metrics and fine-tune for optimal results.
  • Experienced on Data Science models, statistics

Preferred Qualifications:

  • Experience with Monorepos
  • Experience with large language models (LLMs) and advanced deep learning techniques.
  • Knowledge of additional cloud platforms and tools (e.g., Azure, Google Cloud).


 

Key Skills
Education

Any Graduate

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