Generative Ai Specialist at CLOUDRAY INC
Indiana, Indiana, USA -
Full Time


Start Date

Immediate

Expiry Date

08 Aug, 25

Salary

0.0

Posted On

08 May, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Airflow, Version Control, Vectorization, Indexing, Fine Tuning

Industry

Information Technology/IT

Description

Position: Generative Ai Specialist
Experience: 5+years
Job Type: Contract
Work Mode: Remote
Experience: 5+ years in AI/ML with a focus on Generative AI
The client’s platform uses Generative AI models to summarize and derive insights from vast datasets.
While the team has built a strong foundation, they require an expert in LLMs and dynamic prompting
to create scalable, intelligent solutions and drive AI innovation.

REQUIRED SKILLS:

Strong knowledge of GPT APIs, LangChain, and fine-tuning of LLMs.
Proficiency in vectorization, indexing, and retrieval methods.
Experience with Azure OpenAI, Google AI, or similar platforms.
Debugging skills for AI pipelines and related systems.
Git proficiency for version control in AI/ML projects. Preferred Skills:
Knowledge of Airflow and agent-based LLM chains.
Understanding of front-end integrations for AI-driven visualizations

Responsibilities

Dynamic Prompt Management
Design frameworks for handling dynamic and use-case-specific prompts.
Enhance the efficiency and reliability of AI-driven summarization workflows.
Fine-tuning and Customization
Fine-tune GPT and other LLMs to align with client-specific needs.
Implement advanced RAG methodologies for improved response accuracy.
Embedding and Retrieval Optimization
Develop and optimize vectorization techniques using cosine similarity, dot product, and other
measures.
Design scalable indexing and retrieval pipelines for large datasets.
Git and Collaboration
Use Git for effective version control and model development tracking.
Conduct regular reviews of AI pipelines and ensure efficient debugging practices.
Integration and Insights
Collaborate with the Python team to integrate LLMs seamlessly into the data pipeline.
Generate actionable insights from the summarized data to aid decision-making.

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