Machine Learning Engineer - Python / Hadoop

Vayuz Technologies is seeking a highly skilled Machine Learning Engineer with expertise in Python and a strong understanding of Hadoop and other Big Data technologies. You will be instrumental in developing, optimizing, and deploying sophisticated ML and Deep Learning models, working with complex and imbalanced datasets, and ensuring the reliability and performance of our AI-driven solutions in production environments.

Key Responsibilities

• Data Analysis & Feature Engineering : Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets.
• Model Development & Optimization : Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance.
• Deep Learning Implementation : Design and implement advanced Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Imbalanced Data Handling : Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness.
• Model Deployment & Monitoring : Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics.
• Cross-Functional Collaboration : Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals.
• Statistical & Mathematical Application : Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models.
• Innovation & Research : Stay abreast of the latest advancements in ML and AI, actively bringing in new techniques and research findings to drive innovation within the team and company.

Required Skills

Preferred Skills

Skills Required

Machine Learning, Python Programming, Deep Learning, Tensorflow, Hadoop, Spark