Advanced AI Innovation Strategist

8 hours ago

Madurai, Tamil Nadu, India beBeeArtificial Full time ₹ 15,12,000 - ₹ 2,01,60,000

Unlock the Power of Advanced AI

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The role of a GenAI Specialist at Beinex involves driving innovation by designing and implementing cutting-edge generative AI models that meet client needs. As a specialist in this field, you will be responsible for fine-tuning large language models (LLMs), optimizing scalable machine learning pipelines, and integrating AI into client applications for seamless performance.

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Key responsibilities include:

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  • Develop Next-Gen Generative AI Models: Research, design, and fine-tune state-of-the-art models like Llama, GPT, Stable Diffusion, and Variational Autoencoders (VAEs) to drive business impact.">
  • Enhance AI Capabilities: Implement and optimize LLM fine-tuning, prompt engineering, and AI safety mechanisms to improve model efficiency and usability.">
  • Integrate AI into Products/Services: Work closely with business stakeholders and engineers to embed generative AI solutions into real-world applications, ensuring seamless user experiences.">
  • Optimize for Scale & Performance: Build and refine scalable machine learning pipelines for efficient model deployment, inference, and real-time adaptation.">
  • Stay Ahead of AI Trends: Keep pace with emerging technologies, model architectures, and industry breakthroughs to drive continuous innovation.">
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Requirements and Qualifications

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For this role, we are looking for individuals with:

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  • At least 4-5 years of experience in Data Science with strong exposure to Generative AI.">
  • Experience using machine and deep learning languages, preferably Python, to manipulate data and draw insights from large datasets.">
  • Hands-on experience with LLMs, multimodal AI, and diffusion models for applications in text, image, or speech generation.">
  • Strong proficiency in TensorFlow, PyTorch, Hugging Face Transformers, and OpenAI APIs and custom fine-tuning of LLMs and AIops toolkits.">
  • Familiarity with cloud platforms (AWS, GCP, Azure), model deployment strategies, and GPU optimization.">
  • Ability to work with large-scale datasets, vector embeddings, and retrieval-based AI systems.">
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