AI Innovator

1 day ago

Rajahmundry, Andhra Pradesh, India beBeeGenerative Full time US$ 1,20,000 - US$ 1,40,000

We are seeking a highly skilled generative AI professional to join our team.

The ideal candidate will have expertise in designing and developing AI models that can generate human-like text, images, and other forms of content.

This includes creating architectures, algorithms, and frameworks for generative AI, as well as working with data scientists and product managers to understand project requirements and develop innovative solutions using generative AI technologies such as LLMs (Large Language Models).

Key Responsibilities:

  • Designing and developing AI models: The successful candidate will create architectures, algorithms, and frameworks for generative AI models.
  • Implementing AI models: They will build and integrate AI models into existing systems and applications.
  • Working with LLMs and other AI technologies: The candidate will use tools and techniques like LangChain, Haystack, and prompt engineering to develop and deploy AI models.
  • Data preprocessing and analysis: They will prepare data for use in AI models by cleaning, transforming, and processing it.
  • Collaborating with other teams: The candidate will work closely with data scientists, product managers, and other stakeholders to understand project requirements and develop solutions.
  • Testing and deploying AI models: They will evaluate model performance and deploy them to production environments.
  • Monitoring and optimizing AI models: The candidate will track model performance, identify issues, and optimize models for better results.
  • Staying up-to-date with the latest advancements in Gen AI: They will learn about new techniques, models, and frameworks to stay current in the field.

Required Skills:

  • Strong programming skills in Python: Python is the preferred language for AI development.
  • Knowledge of Generative AI, NLP, and LLMs: The candidate should understand the principles behind these technologies and how to use them effectively.
  • Experience with RAG pipelines and vector databases: They should understand how to build and use retrieval-augmented generation pipelines.
  • Familiarity with AI frameworks and libraries: The candidate should have knowledge of frameworks like LangChain, Haystack, and open-source libraries.
  • Understanding of prompt engineering and tokenization: They should understand how to optimize prompts and manage tokenization.
  • Experience in integrating and fine-tuning AI models: The candidate should know how to deploy and maintain AI models in production environments.
  • Excellent communication and problem-solving skills: They should be able to communicate complex technical concepts to non-technical stakeholders.

Optional Skills:

  • Experience with cloud computing platforms (GCP, AWS, Azure): This can be helpful for deploying and managing AI models.
  • Familiarity with MLOps practices: This can help with building and deploying AI models in a scalable and reliable manner.
  • Experience with DevOps practices: This can help with automating the development and deployment of AI models.

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