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Job Title:\n </strong>\n Machine Learning Engineer (Capital Markets)\n</p>\n<p>\n <strong>\n  ???? Location:\n </strong>\n Hyderabad\n</p>\n<p>\n <strong>\n  ???? Experience:\n </strong>\n 6+ Years\n</p>\n<p>\n ???? About the Role\n</p>\n<p>\n We are looking for a\n <strong>\n  passionate Machine Learning Engineer\n </strong>\n to join our growing team in Hyderabad. In this role, you will design, develop, and deploy\n <strong>\n  scalable ML solutions\n </strong>\n for\n <strong>\n  Capital Markets use cases\n </strong>\n , working with cutting-edge tools in a highly collaborative and innovation-driven environment.\n</p>\n<p>\n ???? Key Responsibilities\n</p>\n<ul>\n <li>\n  Design and implement\n  <strong>\n   robust machine learning models\n  </strong>\n  using modern frameworks\n </li>\n <li>\n  Collaborate with\n  <strong>\n   data scientists, engineers, and business stakeholders\n  </strong>\n  to translate requirements into solutions\n </li>\n <li>\n  Deploy and optimize models using\n  <strong>\n   TensorFlow Serving, TorchServe, ONNX, TensorRT\n  </strong>\n </li>\n <li>\n  Build and manage\n  <strong>\n   ML pipelines (MLflow, Kubeflow, Azure/AWS ML pipelines)\n  </strong>\n </li>\n <li>\n  Work with\n  <strong>\n   large-scale distributed data using PySpark\n  </strong>\n </li>\n <li>\n  Monitor model performance and ensure\n  <strong>\n   continuous improvement and retraining\n  </strong>\n </li>\n <li>\n  Integrate ML models into\n  <strong>\n   production-grade systems\n  </strong>\n </li>\n <li>\n  Contribute to\n  <strong>\n   data engineering best practices and architectural decisions\n  </strong>\n </li>\n <li>\n  Mentor junior team members and support team growth\n </li>\n</ul>\n<p>\n ? Mandatory Skills\n</p>\n<ul>\n <li>\n  Strong proficiency in\n  <strong>\n   Python\n  </strong>\n </li>\n <li>\n  Hands-on experience with ML libraries:\n </li>\n <li>\n  <strong>\n   pandas, NumPy, scikit-learn\n  </strong>\n </li>\n <li>\n  <strong>\n   XGBoost, LightGBM, CatBoost\n  </strong>\n </li>\n <li>\n  <strong>\n   TensorFlow / Keras / PyTorch\n  </strong>\n </li>\n <li>\n  Experience with model deployment tools:\n </li>\n <li>\n  <strong>\n   ONNX, TensorRT, TensorFlow Serving, TorchServe\n  </strong>\n </li>\n <li>\n  Experience with ML lifecycle tools:\n </li>\n <li>\n  <strong>\n   MLflow, Kubeflow, Azure ML / AWS ML Pipelines\n  </strong>\n </li>\n <li>\n  Strong experience with\n  <strong>\n   PySpark / distributed data processing\n  </strong>\n </li>\n <li>\n  Solid understanding of\n  <strong>\n   software engineering principles (Git, version control)\n  </strong>\n </li>\n <li>\n  Strong skills in\n  <strong>\n   data cleaning, EDA, and data visualization\n  </strong>\n </li>\n <li>\n  Excellent problem-solving and analytical abilities\n </li>\n <li>\n  <strong>\n   6+ years of experience\n  </strong>\n  , including\n  <strong>\n   2+ years in ML engineering roles\n  </strong>\n </li>\n</ul>\n<p>\n ???? Nice to Have\n</p>\n<ul>\n <li>\n  Experience in\n  <strong>\n   Capital Markets / Financial Services domain\n  </strong>\n </li>\n <li>\n  Exposure to\n  <strong>\n   production-grade ML systems at scale\n  </strong>\n </li>\n <li>\n  Strong mentoring and communication skills\n </li>\n</ul>\n<p>\n ???? Interested?\n</p>\n<p>\n If you are passionate about building\n <strong>\n  scalable ML systems and solving real-world financial problems\n </strong>\n , we’d love to hear from you!\n</p>\n<p>\n ???? 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