Generative AI Engineer
2 weeks ago
About the Role :We are seeking a skilled Generative AI Engineer to design, build, and deploy cutting-edge AI solutions leveraging Large Language Models (LLMs), Natural Language Processing (NLP), and Generative AI frameworks. The ideal candidate will have a strong understanding of prompt engineering, model fine-tuning, and API integrations with GenAI tools, with additional knowledge in AI/ML algorithms being a plus.Key Responsibilities :- Design and develop Generative AI solutions using LLMs such as GPT, Claude, Gemini, or LLaMA.- Work with NLP pipelines for tasks such as summarization, sentiment analysis, entity extraction, and text generation.- Implement fine-tuning, prompt optimization, and model evaluation for custom AI applications.- Integrate and deploy AI models via APIs, SDKs, or microservices for production environments.- Collaborate with data scientists, ML engineers, and product teams to build AI-driven applications and prototypes.- Research and stay updated on the latest advancements in Generative AI, LLMs, and transformer architectures.- Contribute to model performance improvements through data preprocessing, embeddings, and hyperparameter tuning.- Document architectures, model behaviors, and experiment results for reproducibility and scalability.Required Skills & Qualifications :- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.- Hands-on experience with Generative AI tools and frameworks (OpenAI, LangChain, Hugging Face, Vertex AI, etc.).- Strong expertise in LLMs (GPT, BERT, LLaMA, Falcon, etc.) and NLP techniques.- Proficiency in Python and libraries like Transformers, PyTorch, TensorFlow, or spaCy.- Experience in building prompt pipelines, RAG (Retrieval-Augmented Generation), or chatbot solutions.- Familiarity with vector databases (FAISS, Pinecone, Chroma, etc.) for contextual data retrieval.- Strong understanding of data preprocessing, tokenization, and embedding models.Good to Have :- Experience in Machine Learning and Deep Learning model development and deployment.- Knowledge of cloud-based AI platforms (AWS Sagemaker, Azure AI, Google Cloud Vertex AI).- Understanding of MLOps, CI/CD pipelines, and model monitoring.- Exposure to multimodal models (text-to-image, text-to-audio, etc.). (ref:hirist.tech)
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