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Data Science Platform Developer

1 week ago

Remote, India Talpro Full time

Job Summary:

Talpro is seeking an experienced Machine Learning Platform Engineer to join our team. As a Machine Learning Platform Engineer, you will play a critical role in designing, building, and maintaining the infrastructure and pipelines that power our machine learning models and data processing workflows.

Main Responsibilities:

  1. Develop robust and efficient code for machine learning models and data pipelines using Python and associated frameworks.
  2. Build infrastructure as code using tools such as Terraform or equivalent, ensuring scalable and reliable deployment of resources.
  3. Design and implement CI/CD pipelines using technologies like Tekton, Jenkins, GitActions, or GCP Cloud Functions, ensuring smooth and automated software delivery.
  4. Develop API services to enable seamless integration of machine learning models and pipelines into various applications and platforms.
  5. Take MVP/PoC solutions and elevate them to production-level services and mature products.
  6. Conduct end-to-end testing across all stages of development to ensure first-time-right implementations.
  7. Manage deployment platforms for various machine learning models, ensuring modularity and efficiency.
  8. Integrate machine learning features into large-scale products and platforms, collaborating with cross-functional teams.
  9. Create and manage large-scale data transformation pipelines, enabling efficient data processing and analysis.
  10. Orchestrate pipelines using tools like Airflow and Kubeflow, both for structured and unstructured data workflows.
  11. Develop an EDA (Exploratory Data Analysis) automation framework that can be leveraged at scale for data insights.

Requirements:

  • Minimum of 3+ years of hands-on experience in Google Cloud Platform (GCP) with expertise in components such as Astronomer, SQL, Pyspark, Scikit, Github, and VertexAI.
  • At least 3+ years of experience in Python programming, with a strong understanding of its libraries and frameworks.
  • Proven ability to convert complex requirements into practical technical solutions.