AI ENGINEER

$166,400 - $208,000/Yr

Harnham - New York, NY

Full-time - Entry Level

Remote - New York, NY

Professional, Scientific, and Technical Services

About the position

The AI Engineer position is a 6-month contract role focused on developing, designing, and deploying large language models (LLMs) and conversational AI models for IoT-enabled devices. The role is fully remote and requires collaboration during Eastern Standard Time (EST) hours. The engineer will be responsible for creating seamless interactions between users and IoT devices, optimizing machine learning algorithms, and contributing to the full DevOps lifecycle.

Responsibilities

• Design and implement function calling within conversational AI models, enabling seamless interactions between users and IoT devices.
• Deploy AI models and agents into production and scale them into robust, user-facing products.
• Train, fine-tune, and deploy LLMs into production settings.
• Optimize and scale machine learning algorithms to handle large volumes of data efficiently.
• Utilize knowledge graph systems and Retrieval-Augmented Generation (RAG) to create efficient, real-time support agents leveraging technical documentation.
• Integrate data from IoT devices and external sources to deliver intelligent, context-aware responses.
• Contribute to the full DevOps lifecycle, including containerization, CI/CD pipelines, and scaling solutions for deployment.
• Develop and fine-tune LLMs and NLP models that enhance interactions with IoT systems, focusing on domain-specific tasks such as technical support, product monitoring, and customer engagement.

Requirements

• Expertise in designing and implementing function calling within conversational AI models for seamless user-IoT device interactions.
• Up to 3 years of AI development experience, bringing a fresh perspective and a passion for innovative product creation.
• Proven experience deploying AI models and agents into production and scaling them into robust, user-facing products.
• Practical knowledge of DevOps, including containerization (Docker, Kubernetes) and CI/CD workflows for efficient deployment.
• Experience with LLMs (e.g., GPT-4, Whisper), including training, fine-tuning, and application in production settings.
• Experience with contemporary AI and NLP libraries and frameworks (e.g., LangChain, LangGraph, Azure Speech-to-Text).
• Comfortable working with cloud platforms (e.g., AWS, Azure).