AI Engineer

Cardinal Integrated • Santa Clara, CA

56d • Onsite

About The Position

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.

Requirements

• 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.
• Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow and PyTorch.
• Design, develop, and deploy AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models
• Hands-on experience with RAG architectures, including document chunking, embedding generation, and retrieval systems

Nice To Haves

• 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.
• Familiarity with multi-modal AI (text, image, audio).

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.

What This Job Offers

• Career Level: Mid Level
• Industry: Professional, Scientific, and Technical Services
• Number of Employees: 11-50 employees