Genetic Model Architect

2 days ago

Kozhikode, Kerala, India beBeeInnovator Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
AI Innovator Role

The role of an AI Innovator at a forward-thinking organization revolves around designing and implementing cutting-edge generative AI models to meet business objectives.

  • Design Advanced AI Models: Research, develop, and fine-tune state-of-the-art models such as Llama, GPT, Stable Diffusion, and 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: Collaborate with cross-functional teams to embed generative AI solutions into real-world applications, ensuring seamless user experiences.
  • Optimize for Scale & Performance: Develop and refine scalable ML pipelines for efficient model deployment, inference, and real-time adaptation.
  • Stay Ahead of AI Trends: Stay updated on emerging technologies, model architectures, and industry breakthroughs to drive continuous innovation.
  • Communicate Complex AI Concepts: Effectively communicate complex AI concepts to both technical and non-technical audiences, aligning with business strategies.
Required Skills and Qualifications

Key skills requirements include:

  • At least 4-5 years of experience in Data Science domain with strong exposure to Generative AI.
  • Experience using Machine and Deep Learning languages, preferably Python and R, to manipulate data and draw insights from large data sets.
  • 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.
  • Experience building data pipelines and data centric applications using distributed storage platforms in a production setting.
  • Ability to work with large-scale datasets, vector embeddings, and retrieval-based AI systems.

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