Generative AI Engineer

Generative AI Engineer

Client is seeking a Generative AI Engineer as a backfill of 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.

Requirements:

• Needs someone with ~2 years of Generative AI experience - working with LLMs, RAG, MCP use cases like chatbot, OCR, document intelligence (does not need to be agentic).
• Should also have some classic ML predictive modeling - classification, regression models.
• Needs experience in bringing things into production and supporting them for a time in production, not just POC development.
• Should understand model evaluation frameworks, model drift, how to react to model performance changes in prod.
• Computer vision is not a hard requirement right now, but would be useful to have this experience as they move deeper into use cases like OCR - document scanning, extraction of image data to convert to tabular, etc.
• Data Engineering knowledge is needed - theirs is a large Hadoop environment where data is stored for this team to use. This candidate needs experience in SQL to be able to analyze the data, generate datasets. Experience in ETL is nice to have. Should have ability to learn the ETL aspect and willingness to learn.
• Ideally looking for 4-5 years of experience - 2 in Gen AI with 2 in a previous discipline (traditional ML/Data Science, Python Dev, Data Engineering, etc.).
• Open to lighter candidates who we feel strongly about - ~2 years of total experience in Gen AI, as along as they check the boxes and are eager to learn, have a good attitude.

Interview Process:

• 2 rounds:
  • First round is conversational, technical questions and soft skills fit.
  • Second round is onsite, whiteboarding and problem solving.

Must Have:

• Generative AI (experience in chatbots, document extraction, summarization)
• LLMs
• RAG
• Traditional Machine Learning (predictive modeling, regression, classification models)
• Python
• SQL

Nice to Have:

• ETL (particularly on Hadoop)
• Computer Vision
• MCP