Python Developer

• Design, develop, and maintain machine learning models using Python, ensuring optimal performance and scalability.
• Implement algorithms for various AI-driven applications such as natural language processing, computer vision, recommendation systems, etc.
• Collaborate with data scientists and engineers to create data pipelines for processing and analyzing large datasets.
• Analyze and visualize data to derive actionable insights and build predictive models.
• Build and deploy ML models using platforms such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Optimize model performance, including hyperparameter tuning and cross-validation techniques.
• Ensure seamless integration of AI/ML models into production systems.
• Keep up-to-date with the latest advancements in AI ML technologies and best practices.
• Troubleshoot and debug code to resolve issues and improve performance.
• Document your work and present findings to non-technical stakeholders.
• Qualifications:Bachelor s or Master s degree in Computer Science, Engineering, Mathematics, or a related field.
• Proven experience as a Python Developer with strong proficiency in Python and related libraries (e.g., NumPy, Pandas, Matplotlib).
• Hands-on experience in building and deploying machine learning models.
• Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, NLP, etc.
• Proficient in ML libraries and frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras.
• Experience with data processing frameworks like Apache Spark, Hadoop, or similar is a plus.
• Solid understanding of data structures, algorithms, and computational complexity.
• Experience with cloud platforms (AWS, Azure, Google Cloud) for deploying AI/ML solutions.
• Familiarity with version control systems such as Git.
• Strong problem-solving skills and the ability to work in a fast-paced environment.
• Excellent communication skills and the ability to work collaboratively with cross-functional teams.

Preferred Skills:

• Experience in deploying models in production environments.
• Knowledge of AI ethics, bias reduction, and explainability in models.
• Familiarity with containerization tools like Docker and Kubernetes.
• Understanding of data engineering concepts and pipelines.