- Design, build, and deploy machine learning models and AI-powered applications using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).

Integrate with Third-Party APIs :

- Connect and interact with external services and platforms through their APIs to retrieve and send data, leveraging libraries like requests.

API Development & Management :

- Design, develop, and maintain secure and efficient RESTful APIs for internal and external consumption, including authentication, authorization, and error handling.

Data Handling & Processing :

- Work with various data sources, including databases (SQL/NoSQL) and external APIs, to extract, transform, and load data for AI model training and application functionality.

Code Development & Optimization :

- Write clean, efficient, well-documented, and scalable Python code, adhering to best practices and performing code reviews.

Troubleshooting & Debugging :

- Identify and resolve issues related to application functionality, API integrations, and AI model performance.

Collaboration :

- Work closely with cross-functional teams (e.g., product managers, data scientists, front-end developers) to gather requirements and deliver integrated solutions.

Stay Updated :

- Keep abreast of the latest advancements in Python, AI/ML, and API technologies.

Required Skills and Qualifications :

Proficiency in Python :

- Strong command of Python programming, including object-oriented programming (OOP) principles, data structures, and algorithms.

AI/ML Expertise :

- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch), deep learning concepts, natural language processing (NLP), or other relevant AI domains.

API Integration :

- Proven experience integrating with and consuming various third-party APIs, including understanding of API authentication methods (e.g., OAuth, API keys).

API Development :

- Experience in designing and developing RESTful APIs using frameworks like Flask, Django, or FastAPI.

Database Knowledge :

- Familiarity with relational (e.g., PostgreSQL, MySQL) and/or NoSQL databases (e.g., MongoDB).