We are seeking a highly motivated and passionate customer experince program manager with expertise in AI and machine learning technology. This is a customer-facing, hands-on technical role that spans design, build, and operate, with a focus on solving customer problems and removing technical blockers or adoption challenges in AI.

As the customer experince program manager, 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.

Our team is diverse, inclusive, and mission driven. We encourage a growth mindset and prioritize innovation in our work.

As the customer experince program manager, 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.