Generative AI Engineer

5 days ago

Noida, India HR BEES Consultants Full time

AI Engineer :In this role, we are seeking a highly skilled and experienced AI Engineer with hands-on expertise inGenerative AI, AWS Bedrock, Azure Open AI, Document Intelligence tools, Huggingface, Agentic AI, andAdvanced Data Pipelines. It's platforms semantic kernel, autogen, :- Architect and implement advanced generative AI models, focusing on applications such as imageand text generation, image and document extraction, RAG, Prompt engineering, and syntheticdata generation.- Advanced Prompt Engineering techniques. Stay at the forefront of AI/ML and generative AIadvancements, driving the adoption of new technologies and best practices within the team.- Develop, fine-tune, and optimize generative AI models, ensuring they meet performance,scalability, and business objectives. Firm grasp on tools to compare outputs of each model andcompare against each other.- Apply solid data science principles to enhance AI/ML models, using statistical analysis andmachine learning techniques to improve model accuracy and efficiency.- Work closely with data engineers, software developers, and product managers to integrategenerative AI models into products and services, aligning with business objectives.- Ensure that AI models are designed and deployed with ethical considerations, adhering toindustry standards and regulatory requirements.Minimum Qualifications/Skills :- Bachelors or Masters degree in computer science, AI, Machine Learning, Data Science, or arelated field, with 5+ years of experience in AI/ML, particularly with generative AI models.- Strong expertise in developing and deploying generative AI models. Proficiency in Python andexperience with AI development libraries such as TensorFlow and PyTorch. Experience withAzure OpenAI, Open Source LLMs, and LangChain.- Solid experience in applying data science principles, including statistical analysis, datapreprocessing, and machine learning, to enhance AI/ML models.Preferred Qualifications/ Skills :- Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG),fine-tuning, prompt engineering, and zero-shot learning.- Familiarity with NLP or computer vision related to generative AI applications. (ref:hirist.tech)

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