Senior Python Developer

Job Title: Python Developer Job Summary: We are looking for a skilled Python Developer with 7 to 10 years of experience to design, develop, and maintain high-quality back-end systems and applications. The ideal candidate will have expertise in Python and related frameworks, with a focus on building scalable, secure, and efficient software solutions. This role requires a strong problem-solving mindset, collaboration with cross-functional teams, and a commitment to delivering innovative solutions that meet business objectives. Responsibilities Application and Back-End Development: - Design, implement, and maintain back-end systems and APIs using Python frameworks such as Django, Flask, or FastAPI, focusing on scalability, security, and efficiency. - Build and integrate scalable RESTful APIs, ensuring seamless interaction between front-end systems and back-end services. - Write modular, reusable, and testable code following Python’s PEP 8 coding standards and industry best practices. - Develop and optimize robust database schemas for relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB), ensuring efficient data storage and retrieval. - Leverage cloud platforms like AWS, Azure, or Google Cloud for deploying scalable back-end solutions. - Implement caching mechanisms using tools like Redis or Memcached to optimize performance and reduce latency. AI/ML Development: - Build, train, and deploy machine learning (ML) models for real-world applications, such as predictive analytics, anomaly detection, natural language processing (NLP), recommendation systems, and computer vision. - Work with popular machine learning and AI libraries/frameworks, including TensorFlow, PyTorch, Keras, and scikit-learn, to design custom models tailored to business needs. - Process, clean, and analyze large datasets using Python tools such as Pandas, NumPy, and PySpark to enable efficient data preparation and feature engineering. - Develop and maintain pipelines for data preprocessing, model training, validation, and deployment using tools like MLflow, Apache Airflow, or Kubeflow. - Deploy AI/ML models into production environments and expose them as RESTful or GraphQL APIs for integration with other services. - Optimize machine learning models to reduce computational costs and ensure smooth operation in production systems. - Collaborate with data scientists and analysts to validate models, assess their performance, and ensure their alignment with business objectives. - Implement model monitoring and lifecycle management to maintain accuracy over time, addressing data drift and retraining models as necessary. - Experiment with cutting-edge AI techniques such as deep learning, reinforcement learning, and generative models to identify innovative solutions for complex challenges. - Ensure ethical AI practices, including transparency, bias mitigation, and fairness in deployed models. Performance Optimization and Debugging: - Identify and resolve performance bottlenecks in applications and APIs to enhance efficiency. - Use profiling tools to debug and optimize code for memory and speed improvements. - Implement caching mechanisms to reduce latency and improve application responsiveness. Testing, Deployment, and Maintenance: - Write and maintain unit tests, integration tests, and end-to-end tests using Pytest, Unittest, or Nose. - Collaborate on setting up CI/CD pipelines to automate testing, building, and deployment processes. - Deploy and manage applications in production environments with a focus on security, monitoring, and reliability. - Monitor and troubleshoot live systems, ensuring uptime and responsiveness. Collaboration and Teamwork: - Work closely with front-end developers, designers, and product managers to implement new features and resolve issues. - Participate in Agile ceremonies, including sprint planning, stand-ups, and retrospectives, to ensure smooth project delivery. - Provide mentorship and technical guidance to junior developers, promoting best practices and continuous improvement. Required Skills and Qualifications Technical Expertise: - Strong proficiency in Python and its core libraries, with hands-on experience in frameworks such as Django, Flask, or FastAPI. - Solid understanding of RESTful API development, integration, and optimization. - Experience working with relational and non-relational databases (e.g., PostgreSQL, MySQL, MongoDB). - Familiarity with containerization tools like Docker and orchestration platforms like Kubernetes. - Expertise in using Git for version control and collaborating in distributed teams. - Knowledge of CI/CD pipelines and tools like Jenkins, GitHub Actions, or CircleCI. - Strong understanding of software development principles, including OOP, design patterns, and MVC architecture. Preferred Skills: - Experience with asynchronous programming using libraries like asyncio, Celery, or RabbitMQ. - Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, Plotly) for generating insights. - Exposure to machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is a plus. - Familiarity with big data frameworks like Apache Spark or Hadoop. - Experience with serverless architecture using AWS Lambda, Azure Functions, or Google Cloud Run. Soft Skills: - Strong problem-solving abilities with a keen eye for detail and quality. - Excellent communication skills to effectively collaborate with cross-functional teams. - Adaptability to changing project requirements and emerging technologies. - Self-motivated with a passion for continuous learning and innovation.