AI Research Leader

2 days ago

Hyderabad, Telangana, India beBeeMachineLearning Full time ₹ 1,80,00,000 - ₹ 2,50,00,000
Job Title:

A Senior AI Researcher is needed to develop and optimize Machine Learning, NLP, Deep Learning, and Generative AI models.

This role involves working on cutting-edge AI solutions across various industries. A strong background in research and development of innovative AI technologies is required.

The ideal candidate will have a Ph.D. in Computer Science or a related field with expertise in frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.

They must also have experience with Large Language Models (LLMs), model fine-tuning, and prompt engineering.

In addition, the candidate should be proficient in Python, R, or Scala for ML development.

Knowledge of cloud-based ML platforms (AWS, Azure, GCP) and big data processing (Spark, Hadoop, or Dask) is highly desirable.

Key Responsibilities:

  • Develop and optimize Machine Learning, NLP, Deep Learning, and Generative AI models.
  • Research and implement state-of-the-art algorithms for supervised and unsupervised learning.
  • Work with large-scale datasets in distributed environments.
  • Understand business processes to select and apply the best ML approaches.
  • Ensure scalability and performance of ML solutions.
  • Collaborate with cross-functional teams, including product owners, designers, and developers.
  • Solve complex data integration and deployment challenges.
  • Communicate results effectively using data visualization.

Requirements:

  • Ph.D. in Computer Science or a related field.
  • Strong experience in Machine Learning, Deep Learning, NLP, and Generative AI.
  • Hands-on expertise in frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
  • Experience with LLMs (Large Language Models), model fine-tuning, and prompt engineering.
  • Proficiency in Python, R, or Scala for ML development.
  • Knowledge of cloud-based ML platforms (AWS, Azure, GCP).
  • Experience with big data processing (Spark, Hadoop, or Dask).
  • Ability to scale ML models from prototypes to production.
  • Strong analytical and problem-solving skills.

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