Microsoft Principal Machine Learning Engineer 

India, Telangana, Hyderabad 

803880588

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,

• 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.

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