Job
Description
As a Python Developer at Poonawalla Fincorp, you will be responsible for developing and maintaining Python applications using FastAPI, Flask, and libraries like NumPy and Torch. Your role will involve designing schemas using FieldSchema and CollectionSchema in Milvus, integrating Milvus with Python applications for high-performance vector search, and utilizing PyMilvus to manage collections, indexes, and perform vector similarity searches. You will also be expected to implement embedding models (e.g., Deepface, Arcface) to convert raw data into vector representations, build and optimize semantic search, recommendation systems, and image similarity pipelines, and create and manage vector indexes while applying metadata filtering using scalar fields. Documentation of data schemas, workflows, and APIs with clarity will be a key part of your responsibilities. Additionally, you will collaborate with teams to deploy solutions using Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure) and apply your knowledge of Approximate Nearest Neighbor (ANN) algorithms and vector indexing strategies to improve search efficiency. Key Responsibilities: - Develop and maintain Python applications using FastAPI, Flask, and libraries like NumPy, Torch. - Design schemas using FieldSchema and CollectionSchema in Milvus. - Integrate Milvus with Python applications for high-performance vector search. - Utilize PyMilvus to manage collections, indexes, and perform vector similarity searches. - Implement embedding models (e.g., Deepface, Arcface) to convert raw data into vector representations. - Build and optimize semantic search, recommendation systems, and image similarity pipelines. - Create and manage vector indexes and apply metadata filtering using scalar fields. - Document data schemas, workflows, and APIs with clarity. - Collaborate with teams to deploy solutions using Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). - Apply knowledge of Approximate Nearest Neighbor (ANN) algorithms and vector indexing strategies to improve search efficiency. Qualifications Required: - 3-4 years of Python development experience. - Strong proficiency in Python, with experience in FastAPI / Flask, NumPy, Torch. - Hands-on experience with Milvus DB, PyMilvus, and vector database concepts. - Solid understanding of embedding models and vector-based search techniques. - Familiarity with semantic search, recommendation engines, and image similarity pipelines. - Experience with Docker, Kubernetes, or cloud deployment (AWS, GCP, Azure). - Knowledge of ANN algorithms and indexing strategies. - Excellent documentation and communication skills. Company Additional Details: Unfortunately, there were no additional details about the company provided in the job description. As a Python Developer at Poonawalla Fincorp, you will be responsible for developing and maintaining Python applications using FastAPI, Flask, and libraries like NumPy and Torch. Your role will involve designing schemas using FieldSchema and CollectionSchema in Milvus, integrating Milvus with Python applications for high-performance vector search, and utilizing PyMilvus to manage collections, indexes, and perform vector similarity searches. You will also be expected to implement embedding models (e.g., Deepface, Arcface) to convert raw data into vector representations, build and optimize semantic search, recommendation systems, and image similarity pipelines, and create and manage vector indexes while applying metadata filtering using scalar fields. Documentation of data schemas, workflows, and APIs with clarity will be a key part of your responsibilities. Additionally, you will collaborate with teams to deploy solutions using Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure) and apply your knowledge of Approximate Nearest Neighbor (ANN) algorithms and vector indexing strategies to improve search efficiency. Key Responsibilities: - Develop and maintain Python applications using FastAPI, Flask, and libraries like NumPy, Torch. - Design schemas using FieldSchema and CollectionSchema in Milvus. - Integrate Milvus with Python applications for high-performance vector search. - Utilize PyMilvus to manage collections, indexes, and perform vector similarity searches. - Implement embedding models (e.g., Deepface, Arcface) to convert raw data into vector representations. - Build and optimize semantic search, recommendation systems, and image similarity pipelines. - Create and manage vector indexes and apply metadata filtering using scalar fields. - Document data schemas, workflows, and APIs with clarity. - Collaborate with teams to deploy solutions using Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure). - Apply knowledge of Approximate Nearest Neighbor (ANN) algorithms and vector indexing strategies to improve search efficiency. Qualifications Required: - 3-4 years of Python development experience. - Strong proficiency in Python, with experience in FastAPI / Flask, NumPy,
