1. Backend development:
- Design, develop, and maintain scalable backend architectures.
- Implement and optimize RESTful APIs & WebSockets.
- Work with authentication (OAuth, JWT) and role-based access control.
- Optimize backend for performance, scalability, and security.
2. Database management:
- Design and manage relational (PostgreSQL/MySQL) and NoSQL (MongoDB, Redis) databases.
-Write optimized SQL queries and manage data pipelines.
- Handle database migrations, indexing, and query optimization.
3. AI/ML integration:
- Develop APIs for serving ML models efficiently.
- Optimize AI inference pipelines for low latency.
- Work with vector databases (FAISS, Pinecone, Weaviate) for AI applications.
- Implement and deploy ML models using FastAPI, Flask, or Django.
4. Python development & optimization:
- Write clean, efficient, and scalable Python code.
- Work with Python-based backend frameworks like FastAPI, Flask, Django.
- Optimize Python scripts for efficiency and speed.
5. Cloud & deployment:
- Deploy applications using Docker, Kubernetes, AWS/GCP/Azure.
- Set up CI/CD pipelines for smooth deployment.
6. Collaboration & documentation:
- Work with other engineers and ML researchers to integrate AI features.
- Write technical documentation for APIs, databases, and AI models.
Only those candidates can apply who:
1. are available for the work from home job/internship
2. can start the work from home job/internship between 22nd Feb'25 and 29th Mar'25
3. are available for duration of 3 months
4. have relevant skills and interests
1. Strong coding skills, clean coding practices.
2. PyTorch, TensorFlow, or Hugging Face.
3. Fine-tuning, inference optimization, and RAG techniques.
4. Experience with SQL (PostgreSQL, MySQL) & NoSQL (MongoDB, Redis, Vector DBs like FAISS, Pinecone, Weaviate).
5. Experience in designing and integrating RESTful APIs.
6. Ability to write efficient queries and optimize Python code.
7. Basic understanding of Docker, Kubernetes,
8. Can debug and optimize ML models & backend systems.
9. Interested in real-world AI applications.
10. Can work with new tools and technologies as needed.
11. Can document work, explain concepts, and collaborate with teams.
12. Can work independently with minimal supervision.
13. Pursuing or completed a CS, AI/ML, or Data Science degree (or relevant field).
14. Past experience in AI/ML projects – Open-source contributions, research papers, or personal projects in AI/ML.
15. Familiarity with RAG-based applications – Experience with document retrieval, embeddings, or chatbot systems.
We at AerozonAI provide excellent world-leading Cyber Security to your organization, with expertise in AI technology.
