Senior Data Scientist/AI Engineer

Amtex Systems Inc is an information technology and talent solutions company offering talent and BI consulting to the companies in US for over 25 years.

Our solutions are designed to fill resource gaps, by providing the right candidates who deliver value to the organization. Our propensity to nurture and build strong relationships with our clients helps us better understand their business demands and gives us the ability to provide services that are on time and rise above the rest.

Update: Role is Hybrid and will require 3 Days onsite and 2 Days remote.

Must-Have Experience:

Candidates must have:

1. Production deployment of a Gen AI system in a professional environment.
2. RAG pipelines experience.
3. Fine-tuning language models for Gen AI applications.

***Screening questions to ask candidates during our interview***

1. Can you provide examples of Gen AI based solutions that you have built?

Check that candidate has used latest GenAI models, built solutions using RAG based approaches, chatbots, information extraction, question answering based solutions.

1. Have you tuned language models for GenAI applications? What techniques did you use? See if they finetuned any model, they used techniques such as loRA, qlora, peft.
2. Describe your experience with prompt engineering. How have you optimized prompts to get desired outputs from large language models?

What kind of prompt engineering techniques have they used, zero shot, few shot, chain of thought, react, etc

1. What types of vector databases have you used to power GenAI applications?

Candidates have used vector databases such as pinecone, chroma, qdrant, opensearch, mongo vector db, elastic vector db, fiass

1. How have you evaluated the performance and safety of your GenAI solutions? Check for What metrics did you use, and how did they validate the outputs. Do they mention metric such as ROUGE, BLUE, F1 score, groundedness, faithfulness, answer relevancy, context relevancy etc
2. Have you deployed GenAI models to production environments? Have experience deploying these solutions, built APIs around the model. We want candidate who has experience putting these models in production not just worked on a POC

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