Looking for AI/ML Engineer - Onsite at Hartford

Intone Networks - Hartford, CT

Full-time

Hartford, CT

Professional, Scientific, and Technical Services

About the position

The AI/ML Engineer position at Hartford focuses on developing and implementing machine learning models and solutions, particularly in natural language processing (NLP). The role requires strong programming skills in Python and experience with various AI technologies, including cloud services and vector databases. The engineer will work on building intelligent solutions using large language models (LLMs) and will be involved in prompt engineering and evaluation of NLP models.

Responsibilities

• Develop and implement machine learning models using Python and relevant libraries.
• Utilize Jupyter Notebook for interactive coding and data analysis.
• Leverage Google Cloud AI technologies for project development.
• Apply natural language processing techniques using Hugging Face pipelines.
• Build semantic search and retrieval systems using LLM frameworks like LLamaIndex or Langchain.
• Design and structure prompts for LLMs using APIs from OpenAI and Azure.
• Manage and utilize vector databases for efficient similarity search.
• Evaluate the performance of NLP models using standard metrics.
• Integrate Azure AI services into CI/CD pipelines for deployment.
• Provision and manage Azure AI resources effectively.

Requirements

• Strong proficiency in Python for data exploration and analysis.
• Experience with libraries such as Pandas, Matplotlib, and Scikit-Learn.
• Hands-on experience with Jupyter Notebook for coding.
• Deep understanding of natural language processing concepts.
• Experience with Hugging Face pipelines for NLP tasks.
• Familiarity with LLM frameworks like LLamaIndex or Langchain.
• Ability to design prompts for LLMs programmatically.
• Knowledge of vector databases like PineCone, Qdrant, or Weaviate.
• Familiarity with NLP evaluation metrics for model performance.
• Experience with Azure AI services and resource management.
• Proficiency in integrating Azure AI into CI/CD pipelines.
• Experience with containerized deployments on Azure.

Nice-to-haves

• Experience with Google Cloud AI technologies.
• Familiarity with Azure OpenAI Service and Azure AI Search.
• Knowledge of cost management and security best practices in Azure.