Python GEN AI Developer

Summary
We are seeking a highly skilled Senior Generative AI Developer to join our AI/ML team. This role focuses on leveraging cutting:edge Generative AI (GenAI) technologies to drive innovation and efficiency in software development and business processes. The ideal candidate will work on advanced techniques such as Retrieval:Augmented Generation (RAG), document chunking, and data embedding across multiple vector databases. They will collaborate closely with cross:functional teams to design, implement, and optimize AI:driven solutions, with exposure to cloud:native AI platforms like Amazon Bedrock and Microsoft Azure OpenAI considered a plus
Your role in our mission
Essential Job Functions
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Develop and deploy GenAI:based applications to solve complex business problems.
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Implement RAG frameworks to enhance information retrieval and response accuracy.
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Design and optimize document chunking strategies tailored to specific data types and use cases.
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Build and manage data embeddings using various vector databases for high:performance similarity searches.
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Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
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Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.
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Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.
What were looking for
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Proficiency in Generative AI frameworks and technologies like
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Prompt Engineering : creating specific prompts to guide LLM outputs
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Fine Tuning and Few:Shot learning : Adapting LLMs for domain:specific tasks.
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Retrieval:Augmented Generation (RAG) : Combining LLMs with external data retrieval systems
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Text:to:Text Transfer Transformation (T5) : Framework for translating tasks into text forms.
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Expertise in designing and implementing chunking strategies for diverse datasets.
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Strong knowledge of data embedding techniques and working experience with vector databases like Pinecone, Weaviate, or Milvus.
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Solid programming skills in Python, with experience in AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
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Familiarity with cloud platforms and services for AI/ML workloads (AWS or Azure).
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Experience with API integration for AI services and building scalable applications
What you should expect in this role
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:
Develop and deploy GenAI:based applications to solve complex business problems.
:
Implement RAG frameworks to enhance information retrieval and response accuracy.
:
Design and optimize document chunking strategies tailored to specific data types and use cases.
:
Build and manage data embeddings using various vector databases for high:performance similarity searches.
:
Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
:
Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.
:
Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.

Job Type: Permanent