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Microsoft Senior Machine Learning Engineer 
India, Karnataka, Bengaluru 
111355109

16.07.2024
Qualifications

Required:

  • Min 8 years of relevant e-xperience
  • Depth in Data Science, Generative AI and Engineering
  • Background in machine learning, deep learning, and natural language processing
  • Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch)
  • Experience with transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion)
  • Good understanding of statistics, linear algebra, and probability theory
  • Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computing
  • Excellent problem-solving skills and the ability to work independently and collaboratively

Preferred:

  • Preferred training & fine-tuning experience on large data

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Responsibilities

As a (Senior) Machine Learning Engineer in our team, you will:

  • Collaborate with researchers and data scientists to design sophisticated machine learning models
  • 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, and AI research
  • Work with large-scale datasets, preprocess them, and create appropriate data representationsSelect relevant features and ensure data quality for training and evaluation
  • 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