Technical Team Leader- IT-India

Responsibilities:

• Develop and maintain automation scripts and tools using Python, with an emphasis on efficiency and reliability.
• Implement and optimize automation workflows using Selenium, Pandas, Openpyxl, and Win32 to streamline repetitive tasks and increase productivity.
• Utilize Python to manipulate and analyze large datasets, performing data cleaning, transformation, and statistical analysis.
• Design and develop high-quality Python web applications using Django and Flask frameworks.
• Design and implement machine learning models for various applications, including predictive analytics, classification, and regression tasks.
• Explore and experiment with cutting-edge AI techniques, including Computer Vision, NLP, and Generative AI, to develop innovative solutions.
• Collaborate with cross-functional teams to integrate AI models and technologies into existing products and systems.
• Participate in the entire software development lifecycle, from concept and design to testing and deployment, ensuring code quality and performance.
• Stay up-to-date with the latest advancements in Python development, automation, data science, and AI technologies, and apply them to enhance our projects.
• Provide mentorship and technical guidance to junior team members, fostering a culture of continuous learning and growth.
• Assist in DevOps tasks, such as deployment, monitoring, and infrastructure management (knowledge of DevOps is a bonus).

Key Technologies:

• Python - Proficient in Python programming and its ecosystem, including latest versions and features.
• Automation - Extensive experience in developing automation scripts and tools using Python, Selenium, Pandas, Openpyxl, and Win32.
• Data Science - Strong background in data manipulation, analysis, and visualization using Python and libraries like Pandas, NumPy, and Matplotlib.
• Machine Learning - Hands-on experience in designing and implementing machine learning models using libraries such as scikit-learn and TensorFlow.
• Artificial Intelligence - Practical knowledge of AI concepts and experience in applying them in real-world projects, including Computer Vision, NLP, and Generative AI.
• Computer Vision - Experience in working with computer vision libraries like OpenCV to develop applications for image and video analysis.
• Natural Language Processing - Proficiency in NLP techniques and libraries such as NLTK, spaCy, or Transformers for text analysis and language modeling.
• Generative AI - Familiarity with Generative Adversarial Networks (GANs) and related algorithms for generating synthetic data and creative content.
• DevOps (Bonus) - Understanding of DevOps practices and tools such as Docker, Kubernetes, and CI/CD pipelines for efficient software deployment and management.
• Version Control - Experience with version control systems like Git to manage code repositories and collaborate effectively in a team.