AI/ML Engineer Generative AI Specialist UST

5.0 - 9.0 years

0 Lacs

chennai, tamil nadu

On-site

As an AI/ML Engineer Generative AI Specialist with over 5 years of experience, you will be expected to possess the following must-have skills: You should have a strong background in AI/ML frameworks such as PyTorch, TensorFlow, and proficient in Python programming. Your experience with AWS services, specifically AWS Bedrock and Lambda functions, will be crucial. Hands-on expertise in LangChain components (agents, chains, memories, parsers, document loaders), developing and optimizing GenAI, NLP models, and CrewAI is essential for this role. You should be capable of building and deploying RAG (Retrieval-Augmented Generation) systems, chatbots, and AI applications using OpenAI APIs, Ollama, Llama, and llamaparse. Advanced prompt engineering techniques like Chain of Thought (CoT) prompting should be within your skill set. Additionally, experience with Docker, CI/CD pipelines, YML files, and GitHub repository management is required. A strong understanding of system design principles, focusing on security, scalability, and performance optimization, is a must. Good-to-have skills include experience in responsible AI practices, knowledge of event-driven architecture, and familiarity with cloud deployments and Kubernetes. Experience with large-scale AI model training and fine-tuning would be beneficial. Your key responsibilities will involve designing and implementing AI/ML solutions using cutting-edge technologies to ensure scalability, efficiency, and alignment with business objectives. You will be responsible for developing and optimizing LangChain components, CrewAI, GenAI, and NLP models customized to specific applications. Building and deploying production-ready RAG systems, chatbots, and AI-driven applications utilizing OpenAI APIs, Ollama, Llama, and llamaparse will be part of your role. Leveraging AWS Bedrock and other AWS services to deliver high-performance AI solutions is crucial. You will need to apply prompt engineering techniques like Chain of Thought (CoT) prompting to enhance AI interactions, maintain CI/CD pipelines, manage YML files, and utilize GitHub for version control. Implementing containerization using Docker and deploying AI solutions in cloud environments will also fall under your responsibilities. Ensuring that solutions adhere to best practices in system design, focusing on security, performance, and efficiency considerations is essential. You will also need to incorporate responsible AI practices and ensure compliance with ethical AI guidelines. Collaboration with cross-functional teams to translate AI insights into impactful solutions and effective communication of complex technical concepts to both technical and non-technical stakeholders will be expected from you.,

Posted 3 days ago

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