Machine Learning Engineer - Python/Hadoop

Responsibilities:

• Conduct feature engineering, data analysis, and data exploration to extract valuable insights.
• Develop and optimize Machine Learning models to achieve high accuracy and performance.
• Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness.
• Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback.
• Collaborate with cross-functional teams to align ML solutions with business goals.
• Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models.
• Bring in the latest advancements in ML and AI to drive innovation.

Required Skills:

• 4-5 years of hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing.
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks.
• Strong mathematical and statistical knowledge with problem-solving skills.
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Skills:

• Experience with Big Data technologies (e.g., Hadoop, Spark).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices.
• Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.