ResponsibilitiesDesign and develop AI/ML solutions using LLMs, NLP, and Deep Learning modelsBuild and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databasesDevelop and deploy CNN–RNN based architectures for multimodal applic..
Responsibilities
Design and develop AI/ML solutions using LLMs, NLP, and Deep Learning models
Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases
Develop and deploy CNN–RNN based architectures for multimodal applications (vision, speech, text)
Integrate AI models into production systems via REST APIs and microservices
Develop scalable backend services using Python
Deploy, monitor, and maintain AI solutions on AWS (or other cloud platforms)
Build and manage end-to-end ML pipelines, including data ingestion, training, evaluation, and inference
Optimize model performance for latency, scalability, and cost efficiency
Collaborate with cross-functional teams to translate business requirements into AI solutions
Implement CI/CD pipelines for model deployment and continuous integration
Ensure best practices in model governance, security, and compliance
Requirements
3+ years of programming experience in Python
Strong hands-on experience with LLMs (Eg: Claude)
Experience building RAG pipelines and vector search systems
Solid understanding of Machine Learning & Deep Learning concepts
Experience with CNN, RNN, or Hybrid architectures
Experience in Natural Language Processing (NLP)
Experience with REST APIs and Microservices architecture
Hands-on experience with AWS services
Experience with Docker and CI/CD tools, GitHub, Jenkins
Experience with frameworks like TensorFlow or PyTorch
Experience with LangChain, LangGraph, or AI agent frameworks
Experience with multimodal AI systems
Experience in data pipelines and distributed systems
