Requirements 
<ul>
<li>4+ years of hands-on experience in Data Science, AI/ML, or related fields, with a proven record of delivering production-grade NLP and Generative AI solutions.</li>
</ul>

<ul>
<li style="margin-left:0px;">Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA, Mistral) and hands-on experience with advanced fine-tuning methods such as PEFT, LoRA, and prompt engineering.</li>
</ul>

<ul>
<li style="margin-left:0px;">Strong expertise in designing and implementing Retrieval-Augmented Generation (RAG) systems using vector databases like Pinecone, Chroma, FAISS, or similar.</li>
</ul>

<ul>
<li style="margin-left:0px;">Expert-level skills in Python and major ML libraries such as PyTorch, TensorFlow, Hugging Face, and Scikit-learn. Familiarity with backend frameworks (e.g., Flask, Django) for API development is highly desirable.</li>
</ul>

<ul>
<li style="margin-left:0px;">Practical experience applying MLOps principles, including containerization (Docker, Kubernetes), CI/CD automation, and deploying scalable AI systems on AWS, GCP, or Azure.</li>
</ul>

<ul>
<li style="margin-left:0px;">Strong problem-solving, analytical, and research abilities, with the capacity to work independently, manage multiple priorities, and deliver innovative solutions in ambiguous environments.</li>
</ul>

<ul>
<li style="margin-left:0px;">Must possess any graduation degree (Must have Provisional Certificate &amp; Consolidated Marks Memo)</li>
</ul>

<ul>
<li style="margin-left:0px;">Must be willing to work from office &amp; in rotational shifts (5 Working Days &amp; 2 Week Offs)</li>
</ul>

<ul>
<li style="margin-left:0px;">Must be ready to join immediately </li>
</ul>
Job responsibilities 
<ul>
<li style="margin-left:0px;">Lead the end-to-end design, development, and deployment of cutting-edge NLP and Generative AI systems using Large Language Models (LLMs) to address business-critical challenges.</li>
</ul>

<ul>
<li style="margin-left:0px;">Research and implement state-of-the-art AI techniques, including RAG architectures, fine-tuning (PEFT, LoRA), Agentic AI systems, and multi-modal models.</li>
</ul>

<ul>
<li style="margin-left:0px;">Architect and maintain robust, production-grade pipelines for model training, deployment, monitoring, and automated retraining-ensuring system reliability and efficiency.</li>
</ul>

<ul>
<li style="margin-left:0px;">Identify and mitigate issues such as hallucination, bias, and latency. Develop and enforce guardrails, observability metrics, and safety protocols to ensure fair, reliable, and compliant AI solutions.</li>
</ul>

<ul>
<li style="margin-left:0px;">Optimize inference performance through quantization, model distillation, and efficient pipeline design to reduce latency and operational costs.</li>
</ul>

<ul>
<li style="margin-left:0px;">Partner with cross-functional teams, clients, and stakeholders to define requirements, translate business needs into technical deliverables, and deliver tailored AI-powered solutions.</li>
</ul>

<ul>
<li style="margin-left:0px;">Mentor junior data scientists, promote best practices in AI/ML development, and contribute to a culture of continuous innovation and learning. </li>
</ul>

Data Scientist

Requirements 4+ years of hands-on experience in Data Science, AI/ML, or related fields, with a proven record of delivering production-grade NLP and Generative AI solutions. Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA, Mistral) and hands-on experience with advanced fine-tuning methods such as PEFT, LoRA, and prompt engineering. Strong expertise in designing and implementing Retrieval-Augmented Generation (RAG) systems using vector databases like Pinecone, Chroma, FAISS, or similar. Expert-level skills in Python and major ML libraries such as PyTorch, TensorFlow, Hugging Face, and Scikit-learn. Familiarity with backend frameworks (e.g., Flask, Django) for API development is highly desirable. Practical experience applying MLOps principles, including containerization (Docker, Kubernetes), CI/CD automation, and deploying scalable AI systems on AWS, GCP, or Azure. Strong problem-solving, analytical, and research abilities, with the capacity to work independently, manage multiple priorities, and deliver innovative solutions in ambiguous environments. Must possess any graduation degree (Must have Provisional Certificate &amp; Consolidated Marks Memo) Must be willing to work from office &amp; in rotational shifts (5 Working Days &amp; 2 Week Offs) Must be ready to join immediately Job responsibilities Lead the end-to-end design, development, and deployment of cutting-edge NLP and Generative AI systems using Large Language Models (LLMs) to address business-critical challenges. Research and implement state-of-the-art AI techniques, including RAG architectures, fine-tuning (PEFT, LoRA), Agentic AI systems, and multi-modal models. Architect and maintain robust, production-grade pipelines for model training, deployment, monitoring, and automated retraining-ensuring system reliability and efficiency. Identify and mitigate issues such as hallucination, bias, and latency. Develop and enforce guardrails, observability metrics, and safety protocols to ensure fair, reliable, and compliant AI solutions. Optimize inference performance through quantization, model distillation, and efficient pipeline design to reduce latency and operational costs. Partner with cross-functional teams, clients, and stakeholders to define requirements, translate business needs into technical deliverables, and deliver tailored AI-powered solutions. Mentor junior data scientists, promote best practices in AI/ML development, and contribute to a culture of continuous innovation and learning.

Data Scientist in Chennai (UID-15554)

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