Artificial Intelligence Innovator

2 weeks ago

Bharatpur, Rajasthan, India beBeeGenerative Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Drive innovation by designing and implementing advanced generative AI models to meet client needs.

Job Description

The role of GenAI Specialist is to drive business growth through cutting-edge generative AI solutions. Key responsibilities include developing next-generation generative AI models, fine-tuning large language models, and integrating AI into real-world applications for seamless performance.

Key Responsibilities
  • Develop innovative AI models that drive business impact by researching, designing, and fine-tuning state-of-the-art models like Llama, GPT, Stable Diffusion, and Variational Autoencoders (VAEs).
  • Enhance AI capabilities by implementing and optimizing large language model (LLM) fine-tuning, prompt engineering, and AI safety mechanisms to improve model efficiency and usability.
  • Integrate AI into products and services by working closely with business and engineers to embed generative AI solutions into real-world applications.
  • Optimize AI models for scale and performance by building and refining scalable machine learning pipelines for efficient model deployment, inference, and real-time adaptation.
  • Stay ahead of AI trends by keeping pace with emerging technologies, model architectures, and industry breakthroughs.
  • Communicate complex AI concepts to technical and non-technical audiences to ensure alignment with business strategies.
Required Skills and Qualifications
  • 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 large language models, multimodal AI, and diffusion models for applications in text, image, or speech generation.
  • Strong proficiency in TensorFlow, PyTorch, Hugging Face Transformers, and OpenAI APIs, as well as custom fine tuning of large language models 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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