AI Engineer

1 month ago

New York, United States Harnham Full time
AI Engineer

6-Month contract

$80-$100/Hr

Fully Remote - EST Hours

In this position, you'll develop, design, and deploy LLMs and conversational AI models for an IoT-enabled device.

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 LLM's 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.
Qualifications:
  • 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)

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