Data Scientist and Applied Researcher

1 month ago

Bengaluru, Karnataka, India Microsoft Full time

About the Role

We are seeking a highly skilled Data Scientist and Applied Researcher to join our team at Microsoft. As a key member of our ISV AI team, you will play a pivotal role in developing and implementing cutting-edge AI models in client products. Your work will directly contribute to the evolution of Azure ML's state-of-the-art LLM modeling capabilities, enabling customers of AzureML to use GenAI.

Key Responsibilities

  • Implement and fine-tune neural network architectures, including transformer-based models.
  • Optimize model performance, scalability, and efficiency.
  • Conduct experiments to evaluate model performance, robustness, and generalization.
  • Explore novel techniques and approaches to enhance model capabilities.
  • Stay up-to-date with the latest advancements in NLP, deep learning, GenAI, and AI research.
  • Work with large-scale datasets, preprocess them, and create appropriate data representations.
  • Collaborate with cross-functional teams, including researchers, software engineers, and product managers.
  • Communicate technical findings and insights effectively.
  • Deploy trained models in production environments.
  • Monitor model performance, troubleshoot issues, and iterate on improvements.

Requirements

  • A strong background in machine learning, deep learning, and natural language processing.
  • Depth in data science, generative AI, and understanding of data engineering.
  • Experience with transformer-based models (e.g., BERT, GPT, T5, Llama).
  • Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch).
  • Solid understanding of statistics, linear algebra, and probability theory.
  • Experience working with structured and unstructured datasets.
  • Familiarity with cloud platforms (e.g., Azure) and distributed computing.
  • Excellent problem-solving skills and the ability to work independently and collaboratively.

What We Offer

  • Industry leading healthcare
  • Educational resources
  • Discounts on products and services
  • Savings and investments
  • Maternity and paternity leave
  • Generous time away
  • Giving programs
  • Opportunities to network and connect

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