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NLP + OpenCV

Roles & Responsibilities

  • 3+ years of hands-on experience in Google Cloud Platform (GCP) with expertise in Astronomer, SQL, PySpark, Scikit-learn, GitHub, and Vertex AI
  • At least 3+ years of Python programming experience with a strong understanding of its libraries and frameworks
  • Proven ability to translate complex requirements into practical technical solutions

Requirements:

  • Develop robust Python-based code for ML models and data pipelines
  • Build infrastructure as code (Terraform or equivalent) to deploy scalable and reliable resources
  • Design and implement CI/CD pipelines using Tekton, Jenkins, GitHub Actions, or GCP Cloud Functions for automated delivery
  • Develop API services and productionize MVP/PoC solutions into scalable, end-to-end ML platforms, including data transformation pipelines and orchestration with Airflow or Kubeflow

Job description

This is a remote position.

We are seeking a highly skilled and motivated Machine Learning Platform Engineer to join our dynamic 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. Your expertise in Python, cloud technologies, and associated frameworks will be essential in driving the success of our machine learning initiatives.

Responsibilities:

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

Must-Have Skills:

  • 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.

Nice-to-Have Skills:

  • Familiarity with cloud technologies such as Cloud Functions, CloudBuild, and Kubernetes.
  • Experience with Software as a Service (SaS) based models.
  • Knowledge of deep learning frameworks such as PyTorch and TensorFlow.



Salary: 28 LPA

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