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Microsoft Principle AI Customer Technology Advocate 
Japan 
680966637

25.06.2024

As the AI Customer Advocate, you will be responsible for technical customer engagements and will work on the most challenging and exciting projects. You will work with select customers to solve their business problems using AI/ML, which may involve reusing existing models, refining/customizing models, or building new models.

Qualifications
  • BS or MS degree in STEM.
  • 8+ years as a technical solution architect or technical consultant, with some experience with ML or Data expertise
  • Experience in working with cloud-based conversational AI services.
  • Knowledge and demonstrable skills in deep learning architectures and implementation using Pytorch, TensorFlow, or other frameworks.
  • Ability to leverage APIs and other relevant data science & data analytical tools such as Azure Machine learning, Synapse with strong data analytics & debugging skills.
  • Base level understanding of Open AI and Azure Cognitive Services like Speech Services, LUIS, Computer Vision.
  • Comfortable in automated deployments using CI/CD pipelines in Azure DevOps and MLOps.
  • Strong communication skills (verbal and written) with the ability to communicate across teams, internal and external, at all levels.
  • Problem-solving skills with a deep passion and empathy for customers.
Responsibilities

As the AI Customer Advocate, you will focus on large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. You will apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Your responsibilities will include:

  • Work with Azure AI/OpenAI services to build and train models, create custom models for use cases, and optimize custom models.
  • Exposure to ChatGPT and DALL·E 2.
  • Incoming data validation, quality checks, and processing with tooling.
  • End-to-end scenario implementation involving multiple cognitive services and integration with other Azure services.
  • Collaborate with key stakeholders and contribute to the full development life cycle, including requirements analysis, architecture design, testing, and customer POC implementation.
  • Explore and source a wide variety of data as a data enthusiast.
  • Formulate real-world enterprise scenarios into machine learning problems and think of optimal ways of solving.
  • Wrangle large datasets on the cloud to understand the properties of the data.
  • Transform data into innovative features/signals that can improve machine-learning tasks.
  • Participate in end-to-end machine learning model lifecycle, from prototyping, implementing & evaluating ML and DL models, followed by deployment and monitoring using Azure.
  • Work in a team of engineers, data scientists, and UX experts to deliver an intuitive, robust solution to the customer.