
Data Analyst Lead
1 week ago
This is a Mid-Senior level job that requires a strong understanding of data engineering, AI/ML, and cloud-based AI infrastructure. The ideal candidate will have at least 2-4 years of experience in these areas.
The job involves developing and maintaining scalable AI data infrastructure using various tools and technologies, including PySpark, Pandas, SQL, and cloud services like Azure, AWS, and GCP.
You will also be responsible for implementing retrieval-augmented generation (RAG) pipelines using FAISS, ChromaDB, and Pinecone, as well as deploying and monitoring AI applications using FastAPI, Streamlit, Docker, and other tools.
We are looking for a highly skilled professional who can work independently and collaboratively as part of our team.
Required Skills and Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field
- At least 2-4 years of experience in data engineering, AI/ML, or cloud-based AI infrastructure
- Expertise in Python, PySpark, and SQL for data transformation and large-scale processing
- Experience with cloud platforms (AWS, Azure, GCP) for AI model deployment and data pipeline automation
- Hands-on experience with vector databases (FAISS, ChromaDB, Pinecone) for efficient data retrieval
- Proficiency in containerization and orchestration tools like Docker and Kubernetes
- Strong understanding of retrieval-augmented generation (RAG) and real-time AI model deployment
- Knowledge of API development and AI service integration using FastAPI and Streamlit/Dash
- Ability to optimize AI-driven automation processes and ensure model efficiency
- Strong analytical and problem-solving skills
- Excellent communication and collaboration abilities
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