Senior Python Developer (Django, Flask, FastAPI, AI/ML Architect)

Senior Python Developer (Django, Flask, FastAPI, AI/ML Architect) Job Description: We are seeking a highly experienced Senior Python Developer with an architect-level skill set to join our dynamic team. The ideal candidate will have extensive experience building and scaling large web applications using Django, Flask, and FastAPI, and a strong background in AI/ML projects. The role requires proficiency in version control using Git and GitLab, coupled with advanced CI/CD pipeline operations for deploying robust and scalable solutions. Responsibilities:

1. Architect, design, and implement large-scale, high-performance web applications using Django, Flask, and FastAPI frameworks.
2. Lead AI/ML solution development and integrate them into scalable applications.
3. Collaborate with cross-functional teams to translate business requirements into technical solutions.
4. Ensure clean, efficient, and reusable code by implementing best practices and design patterns.
5. Develop and maintain robust CI/CD pipelines using GitLab to streamline code integration and deployment processes.
6. Design and implement scalable microservices and APIs for large-scale applications.
7. Optimize system architecture for performance, reliability, and scalability.
8. Manage and mentor a team of developers, providing technical guidance and code reviews.
9. Handle deployment, monitoring, and management of scalable applications in cloud environments (AWS, Azure, or GCP).
10. Stay updated with emerging technologies and tools in Python, AI/ML, and web development.

1. Technical Skills:
2. Programming Languages: Python (expert level).
3. Frameworks: Django, Flask, FastAPI (extensive experience).
4. AI/ML: Strong understanding of machine learning algorithms, frameworks like TensorFlow, PyTorch, or Scikit-learn, and data analysis tools.
5. Architectural Experience: Designing and deploying large-scale, distributed applications.
6. Version Control: Advanced Git expertise, including GitLab workflows.
7. CI/CD: Proficiency in setting up CI/CD pipelines using GitLab CI/CD, Jenkins, or similar tools.
8. Databases: SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB).
9. Cloud: Deployment experience with AWS, Azure, or GCP.
10. APIs: Building RESTful and GraphQL APIs, ensuring best practices.

1. Familiarity with containerization tools (e.g., Docker, Kubernetes).
2. Experience with monitoring tools like Prometheus, Grafana, or ELK stack.
3. Knowledge of message brokers like RabbitMQ, Kafka, or Celery.
4. Contributions to open-source projects.