AI Innovation Strategist

21 hours ago

Belgaum, Karnataka, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Description

The GenAI Specialist role drives innovation by designing and implementing advanced generative AI models. Responsibilities include fine-tuning Large Language Models (LLMs), optimizing scalable Machine Learning (ML) pipelines, and integrating AI into applications for seamless performance.

This position involves collaborating with stakeholders, communicating complex AI concepts, and staying updated on industry trends to ensure cutting-edge solutions.

To excel in this role, applicants should have a Master's degree in Data Science, Statistics, Engineering, or a related field. A Bachelor's degree with relevant work experience is also acceptable.

Key Responsibilities:
  • Develop Next-Gen 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.
Required Skills:
  • 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 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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