Data Engineer - Machine Learning

As a Data Engineer Machine Learning at our company, you will be responsible for designing and building end-to-end ML pipelines on Google Cloud Platform. You will develop scalable machine learning solutions using Python and ML frameworks, work on Deep Learning and Transformer-based models, and build and optimize data pipelines for ML workflows. Collaboration with stakeholders for requirements gathering and solution design, as well as deploying and maintaining production-grade ML systems, will also be key aspects of your role. Key Responsibilities: - Design and build end-to-end ML pipelines on Google Cloud Platform - Develop scalable machine learning solutions using Python and ML frameworks - Work on Deep Learning and Transformer-based models - Build and optimize data pipelines for ML workflows - Collaborate with stakeholders for requirements gathering and solution design - Deploy and maintain production-grade ML systems Qualifications Required: - 8 years total experience with 7 years of relevant experience - Strong hands-on experience in Python, including OOPs, DSA, and design patterns - Experience with Machine Learning frameworks such as Scikit-learn, XGBoost, and LightGBM - Strong knowledge of Deep Learning using PyTorch and TensorFlow - Experience in NLP Transformers and Generative AI - Hands-on experience with Google Cloud Platform and ML pipeline development - Familiarity with LangChain, LangGraph, LLM APIs (OpenAI Gemini, etc.) is preferred (Note: The duplicate 'Required Skills' section has been omitted from the final Job Description as it is redundant.) As a Data Engineer Machine Learning at our company, you will be responsible for designing and building end-to-end ML pipelines on Google Cloud Platform. You will develop scalable machine learning solutions using Python and ML frameworks, work on Deep Learning and Transformer-based models, and build and optimize data pipelines for ML workflows. Collaboration with stakeholders for requirements gathering and solution design, as well as deploying and maintaining production-grade ML systems, will also be key aspects of your role. Key Responsibilities: - Design and build end-to-end ML pipelines on Google Cloud Platform - Develop scalable machine learning solutions using Python and ML frameworks - Work on Deep Learning and Transformer-based models - Build and optimize data pipelines for ML workflows - Collaborate with stakeholders for requirements gathering and solution design - Deploy and maintain production-grade ML systems Qualifications Required: - 8 years total experience with 7 years of relevant experience - Strong hands-on experience in Python, including OOPs, DSA, and design patterns - Experience with Machine Learning frameworks such as Scikit-learn, XGBoost, and LightGBM - Strong knowledge of Deep Learning using PyTorch and TensorFlow - Experience in NLP Transformers and Generative AI - Hands-on experience with Google Cloud Platform and ML pipeline development - Familiarity with LangChain, LangGraph, LLM APIs (OpenAI Gemini, etc.) is preferred (Note: The duplicate 'Required Skills' section has been omitted from the final Job Description as it is redundant.)