Machine Learning Developer

5 days ago

Bengaluru, Karnataka, India o9 Solutions, Inc. Full time

About o9 Solutions

At o9 Solutions, we aim to revolutionize planning and decision-making for enterprises. Our cutting-edge AI-powered platform, the o9 Digital Brain, drives digital transformations for major global companies.

We're looking for talented Machine Learning Developers to join our fast-paced team. As a key member, you will be responsible for designing and developing scalable machine learning systems that meet our high standards of performance and maintainability.

Key Responsibilities:

  • Software Engineering & Architecture:
    • Write clean, modular, and efficient Python code following best practices.
    • Develop, maintain, and release internal Python packages for ML operations.
    • Evaluate and design scalable ML system architectures, balancing performance, maintainability, and scalability.
    • Refactor and optimize existing codebases for scalability and performance.
    • Follow Git workflow best practices, implement testing strategies, and ensure long-term code maintainability.
  • Machine Learning Development:
    • Apply a strong understanding of machine learning algorithms, especially tree-based models (e.g., LightGBM) to build time-series forecasting models.
    • Design machine learning systems that are scalable and efficient.
    • Engineer and optimize high-quality features for ML pipelines.
    • Conduct model evaluation and tuning to improve performance.
  • MLOps:
    • Build and maintain CI/CD pipelines for ML models and Python package releases.
    • Design and build scalable data pipelines for ingestion and transformation while ensuring data quality, consistency, and efficiency.
    • Deploy and serve models for batch and real-time inference (FastAPI, Flask).

Requirements:

  • 1-5 years of experience in Machine Learning, Software Engineering, or related fields.
  • Bachelor's or Master's degree in Computer Science, AI/ML, or equivalent.
  • Expert-level proficiency in Python, with strong coding skills.
  • Fundamental understanding of various machine learning algorithms, including supervised and unsupervised techniques.
  • Good to have hands-on experience with data pipelines, training/inference, deployment (batch/real-time), model retraining, testing (e.g., unit, regression), and version control.
  • Exposure/experience with Docker.
  • Exposure/experience with Git and Agile methodologies (e.g., Jira/Azure DevOps).

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