Backend Developer - Python

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Responsibilities<\/b>

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• Develop, maintain, and optimize Python -based APIs<\/b> that expose AI/ML functionality for internal and external use.

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• Integrate third -party AI/ML APIs<\/b> (e.g., OpenAI, Google Vertex AI, AWS SageMaker, Hugging Face, ElasticSearch) into our applications.

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• Work with engineering teams<\/b> to deploy, monitor, and scale AI models in production environments.

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• Implement efficient data pipelines<\/b> for model inference, training, and evaluation.

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• Ensure API security, authentication, and authorization using industry standards (OAuth, JWT, API keys).

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• Write high -performance, scalable, and well -documented<\/b> code.

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• Optimize API endpoints for low -latency inference<\/b> and efficient resource utilization.

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• Collaborate with DevOps teams to deploy AI -powered applications using Docker, Kubernetes, and cloud services (AWS/GCP/Azure)<\/b>.

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• Implement logging, monitoring, and error -handling mechanisms for robust API services.

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• Stay updated on emerging AI/ML technologies<\/b> and recommend best practices for API integration.

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  Requirements<\/h3>

  • 3+ years<\/b> of experience in Python development, with expertise in FastAPI, Flask, or Django<\/b>.

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  • Strong understanding of RESTful APIs<\/b>, WebSockets, and API versioning best practices.

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  • Experience integrating AI/ML models using TensorFlow, PyTorch, Scikit -learn, or similar frameworks<\/b>.

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  • Proficiency with third -party AI/ML APIs<\/b> and cloud -based model deployment platforms.

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  • Solid understanding of asynchronous programming (Asyncio), multiprocessing, and API performance tuning<\/b>.

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  • Hands -on experience with PostgreSQL, MongoDB, Redis, or other databases<\/b>.

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  • Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms<\/b>.

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  • Knowledge of authentication and security best practices for API development.

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  • Strong problem -solving skills and ability to work in a fast -paced environment.

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    Nice to Have

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    • Experience with GraphQL APIs<\/b> and real -time data streaming.

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    • Familiarity with LangChain, vector databases (e.g., Pinecone, FAISS), or RAG -based AI architectures<\/b>.

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    • Knowledge of LLMs (Large Language Models) and fine -tuning techniques<\/b>.

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    • Previous experience in MLOps, model monitoring, and AI -driven automation.

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