Gen AI Engineer

Saxon Global • Newark, NJ

1d

About The Position

Seeking a Generative AI Engineer as a backfill for an existing team member to support a range of ongoing and upcoming ML and AI use cases that span summarization, document extraction, chatbots, and more traditional machine learning use cases involving claims and fraud detection. The role requires someone with approximately 2 years of Generative AI experience, working with LLMs and RAG, and MCP use cases like chatbots, OCR, and document intelligence. Experience in classic ML predictive modeling, such as classification and regression models, is also necessary. The candidate should have experience in bringing models into production and supporting them, not just POC development. Understanding of model evaluation frameworks, model drift, and how to react to model performance changes in production is crucial. While computer vision is not a hard requirement, experience in this area would be beneficial for use cases like OCR, document scanning, and extracting image data to convert to tabular formats. Data Engineering knowledge is needed, as the team utilizes a large Hadoop environment for data storage. The candidate must have experience in SQL for data analysis and dataset generation. ETL experience is a plus, and the ability and willingness to learn ETL processes are important. Ideally, the candidate will have 4-5 years of experience, with 2 years in Gen AI and 2 years in a previous discipline (traditional ML/Data Science, Python Dev, Data Engineering, etc.). Lighter candidates with approximately 2 years of total experience in Gen AI will be considered if they meet the core requirements, are eager to learn, and possess a good attitude.

Requirements

• Generative AI experience (chatbots, document extraction, summarization)
• Experience with LLMs
• Experience with RAG
• Traditional Machine Learning experience (predictive modeling, regression, classification models)
• Python proficiency
• SQL proficiency
• Experience bringing models into production and supporting them
• Understanding of model evaluation frameworks
• Understanding of model drift and reacting to performance changes in production
• Data Engineering knowledge
• Experience analyzing data and generating datasets using SQL

Nice To Haves

• ETL experience (particularly on Hadoop)
• Computer Vision experience
• Experience with MCP

Responsibilities

• Support ongoing and upcoming ML and AI use cases including summarization, document extraction, chatbots, and traditional machine learning for claims and fraud detection.
• Develop and implement Generative AI solutions using LLMs and RAG.
• Work with MCP use cases such as chatbots, OCR, and document intelligence.
• Develop and implement classic ML predictive models (classification, regression).
• Bring models into production and provide ongoing support.
• Monitor model performance in production, evaluate models, and address model drift and performance changes.
• Analyze data and generate datasets using SQL.
• Collaborate with data engineering in a Hadoop environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed