JOB SUMMARY:

We are looking for an experienced AI Architect with a strong background in Generative AI & NLP/NLU to lead the design and development of cutting-edge AI solutions. The ideal candidate will have expertise in AI/ML architecture, deep learning frameworks, and retrieval-based AI techniques, with a particular focus on healthcare datasets and industry-specific challenges.

REQUIRED SKILLS & QUALIFICATIONS:

7+ years of experience in AI/ML architecture & development, with a strong focus on Generative AI & NLP/NLU.
Strong proficiency in Python and hands-on experience with TensorFlow/PyTorch for deep learning model development.
Expertise in LangChain, RAG, GraphLLM, and vector databases (Neo4J) for retrieval-based AI solutions.
Experience working with healthcare datasets and a solid understanding of domain-specific challenges.
Familiarity with data engineering tools such as PySpark, Airflow, and Temporal to support AI-driven data pipelines.
Proven ability to develop and fine-tune Transformer-based models (BERT, GPT, T5, Hugging Face Transformers).Strong problem-solving skills and the ability to design scalable AI solutions in a production environment.
Excellent communication and collaboration skills, with experience working in cross-functional teams.
Job Type: Contract
Pay: $50.00 - $60.00 per hour

Schedule:

• Day shift
• Monday to Friday

Application Question(s):

• Are you an US Citizen/GC holder?
• How many years of experience you as an AI Architect?
• How many years of experience you have into the below?
• Generative AI & NLP/NLU
• Healthcare Datasets
• Tensor Flow or Pytorch
• Graph LLM
• Python

Healthcare domain

• What is your Expected Salary on 1099?
• What is the best email and contact number to reach you?

Work Location: Remot

KEY RESPONSIBILITIES:

Design and implement scalable AI/ML architectures, focusing on Generative AI & NLP/NLU solutions.
Develop and optimize Transformer-based NLP models such as BERT, GPT, T5, leveraging Hugging Face Transformers for advanced text understanding and generation.
Work with LangChain, RAG, GraphLLM, and vector databases (Neo4J) to develop retrieval-augmented generation (RAG) models and knowledge-based AI solutions.
Utilize TensorFlow/PyTorch to train and deploy AI models, ensuring performance, scalability, and efficiency.
Process and analyze healthcare datasets, addressing domain-specific challenges such as data privacy, compliance, and structured/unstructured data processing.
Collaborate with data engineering teams, leveraging tools like PySpark, Airflow, and Temporal for efficient data processing and workflow automation.
Stay updated with the latest advancements in AI/ML, NLP, and Generative AI, recommending innovative approaches for AI-driven solutions.
Optimize AI models for deployment in cloud/on-prem environments, ensuring integration with existing enterprise applications.