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As a Generative AI Engineer at InfoObjects, you will design, develop, and deploy advanced AI models that generate content across text, images, and more. You will work closely with data scientists, ML engineers, and business stakeholders to solve real-world problems using state-of-the-art generative models.
Job Responsibility:
Design and implement generative AI models using frameworks like OpenAI, Hugging Face, or custom architectures
Fine-tune large language models (LLMs) and multi-modal models to align with specific client and project needs
Research and apply advanced techniques including prompt engineering, reinforcement learning with human feedback (RLHF), and model optimization
Collaborate with product teams to integrate AI-powered features into scalable applications
Monitor and improve AI model performance through continuous training and evaluation
Contribute to the development of AI best practices and ensure ethical AI adoption
Requirements:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related fields
Strong experience with Python and machine learning frameworks like PyTorch or TensorFlow
Practical understanding of LLMs (GPT, Claude, Llama, Gemini) and generative models (Diffusion Models, GANs)
Hands-on with APIs and platforms such as OpenAI, Hugging Face, LangChain, and Vector Databases (Pinecone, Weaviate, ChromaDB)
Vector DBs: Experience with AWS solutions including Aurora Postgres, and Databricks Mosaic AI Vector Search
Cloud Platforms: Proficiency in AWS, GCP, Azure, and Databricks
Document Processing: Familiarity with tools like Azure AI Document Intelligence
Orchestration: Experience integrating AWS Knowledge Bases for AI pipeline orchestration
Knowledge of model evaluation, fine-tuning, retrieval-augmented generation (RAG), and ethical AI practices
Strong analytical mindset and the ability to solve complex problems creatively
Nice to have:
Contributions to AI research papers, open-source projects, or community forums
Understanding of AI ethics, fairness, and responsible AI practices
Experience deploying models using cloud-native AI services and tools
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