Generative AI Engineer

<p><p><b>Role : </b> Gen AI Engineer<br/><br/><b>Location : </b> Bangalore, Delhi, Hyderabad<br/><br/><b>Working model : </b> Hybrid<br/><br/><b>Key Responsibilities : </b><br/><br/>- Designing and Developing AI models : This includes creating architectures, algorithms, and frameworks for generative AI.<br/><br/>- Implementing AI models : This involves building and integrating AI models into existing systems and applications.<br/><br/>- Working with LLMs and other AI technologies : This includes using tools and techniques like LangChain, Haystack, and prompt engineering.<br/><br/>- Data preprocessing and analysis : This involves preparing data for use in AI models.<br/><br/>- Collaborating with other teams : This includes working with data scientists, product managers, and other stakeholders.<br/><br/>- Testing and deploying AI models : This involves evaluating model performance and deploying them to production environments.<br/><br/>- Monitoring and optimizing AI models : This involves tracking model performance, identifying issues, and optimizing models for better results.<br/><br/>- Staying up to date with the latest advancements in Gen AI : This includes learning about new techniques, models, and frameworks.<br/><br/><b>Required Skills : </b><br/><br/>- Strong programming skills in Python : Python is the preferred language for AI development.<br/><br/>- Knowledge of Generative AI, NLP, and LLMs : This includes understanding the principles behind these technologies and how to use them effectively.<br/><br/>- Experience with RAG pipelines and vector databases : This includes understanding how to build and use retrieval-augmented generation pipelines.<br/><br/>- Familiarity with AI frameworks and libraries : This includes knowledge of frameworks like LangChain, Haystack, and open-source libraries.<br/><br/>- Understanding of prompt engineering and tokenization : This includes understanding how to optimize prompts and manage tokenization.<br/><br/>- Experience in integrating and fine-tuning AI models : This includes knowledge of deploying and maintaining AI models in production environments</p><br/></p> (ref:hirist.tech)