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.