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Job Views:  
207
Applications:  51
Recruiter Actions:  2

Posted in

IT & Systems

Job Code

1626390

Roles & Responsibilities:

- Design, develop, and deploy large language models (LLMs) for both text and voice use cases.

- Implement fine-tuning, prompt engineering, and optimization for domain-specific Gen AI solutions.

- Architect and manage ML systems leveraging neural networks and transformer architectures.

- Drive implementation of Retrieval-Augmented Generation (RAG) systems and AI agents.

- Collaborate with cross-functional teams to build scalable AI products.

- Conduct data preprocessing, model evaluation, and continuous model improvement.

- Lead projects on responsible AI deployment, bias detection, and model governance.

- Mentor junior engineers and contribute to the AI/ML Centre of Excellence.

- Education Qualification & Experience:

- Bachelor's or Master's degree from any Tier 1 institution

- Minimum 5-10 Years of hands-on experience with LLM fine-tuning, prompt engineering, and generative AI frameworks (LangChain, LlamaIndex, AutoGen, CrewAI)

- Deep understanding of Neural Networks and Transformer-based architectures (GPT, BERT, Llama, etc.)

- Experience building AI systems for both Voice and Text modalities

- Proficiency in Python, TensorFlow, PyTorch, Hugging Face, and related ML frameworks

- Strong understanding of RAG systems and vector databases (Pinecone, Weaviate, ChromaDB)

- Expertise in ML Ops, model deployment, and monitoring (Kubernetes, Docker, CI/CD)

- Knowledge of cloud-based AI services (AWS Sagemaker, Azure ML, GCP Vertex AI)

- Familiarity with NLP, Speech Recognition, and Conversational AI

- Sound understanding of AI ethics, governance, and compliance

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Job Views:  
207
Applications:  51
Recruiter Actions:  2

Posted in

IT & Systems

Job Code

1626390

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