AI Innovation Expert

5 days ago

Shimoga, Karnataka, India beBeeGenerative Full time ₹ 25,00,000 - ₹ 30,00,000
Job Title: AI Model Designer

Job Overview:

As an AI Model Designer at a leading tech firm, you will play a pivotal role in shaping the future of artificial intelligence by designing and implementing cutting-edge generative models to meet client needs.

Key Responsibilities:

  • Develop advanced generative AI models: Research, design, and fine-tune state-of-the-art models like 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: Work closely with business and engineers to embed generative AI solutions into real-world applications, ensuring seamless user experiences.
  • Optimize for scale & performance: Build and refine scalable ML 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.
  • Communicate complex AI concepts to technical and non-technical audiences, ensuring alignment with business strategies.

Requirements:

  • 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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