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Microsoft Principal Machine Learning Engineer 
India, Telangana, Hyderabad 
803880588

11.06.2024

a talented and experienced Principal Machine Learning Engineera Thought leaderplay a pivotal role in designing, developing, and implementingAI products. Your work will directly contribute to the evolution of Azure ML’sto useAs a tech lead ybe responsible forand LLM relatedby working with aimplementing core algorithms,


Qualifications
  • Depth inData Science, GenerativeAIand Engineering
  • A strong background in machine learning, deep learning, and natural language processing.
  • Proficiencyin Python and relevant ML libraries (e.g., TensorFlow,PyTorch).
  • Experience with transformer-based models (e.g., BERT, GPT, T5, Llama).
  • Solid understanding of statistics, linear algebra, and probability theory.
  • Experience working with structured and unstructured datasets.
  • Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computing.
  • Excellent problem-solving skills and the ability to work independently and collaboratively.
  • Desired but notrequired:2+ years of experience managingatechnicalteamas a people manager15+ years Overall experience is a must

Why Join Us?

  • Be part of a dynamic team shaping the future of AI and language models.
  • Work on high-impact projects with global reach.
  • Collaborate with leading experts in the field.
  • Enjoy a flexible and inclusive work environment.

Responsibilities

As a (Principal) 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.
  • Optimizemodel performance, scalability, and efficiency.
  • Conduct experiments to evaluate model performance, robustness, and generalization.
  • Explore novel techniques and approaches to enhance model capabilities.
  • Stayup-to-datewith the latest advancements in NLP, deep learning, and AI research.
  • Work with large-scale datasets, preprocess them, and createappropriate datarepresentations.
  • Select 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.
  • As a tech lead, managingapplied science projects