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AI Engineer
Role name: AI Engineer
Location: Santa Clara (Onsite) Contract Role About the Role: We are seeking a highly skilled and innovative AI Engineer to join our team and lead the development of intelligent AI agents and RAG-based applications. This role is ideal for someone passionate about pushing the boundaries of applied AI, with hands-on experience in building scalable, production-grade GenAI systems. Key Responsibilities: • Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI- centric libraries such as TensorFlow and PyTorch. • Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources. • Design, develop, and deploy AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models. • Implement and manipulate complex algorithms essential for developing and optimizing generative AI models. • Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance. • Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows. Required Qualifications: • Bachelor's or master's degree in computer science, AI/ML, or related field. • 3+ years of experience in AI/ML engineering, with at least 1 year focused on Generative AI. • Hands-on experience with RAG architectures, including document chunking, embedding generation, and retrieval systems. • Proficiency in Python and familiarity with libraries such as Hugging Face, Transformers, OpenAI API, and PyTorch or TensorFlow. • Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). • Strong understanding of LLM capabilities, limitations, and prompt engineering techniques. Preferred Qualifications: • Experience with fine-tuning LLMs or training custom models. • Familiarity with multi-modal AI (text, image, audio). • Contributions to open-source GenAI projects or publications in AI conferences. • Experience with CI/CD pipelines for ML model deployment. | ||||||
