The Alexa Machine Learning team’s goal is to make voice interfaces ubiquitous and as natural as speaking to a human. Deep learning at this massive scale requires new research and development. The team is responsible for cutting-edge research and development in virtually all fields of Human Language Technology: Automatic Speech Recognition (ASR), Artificial Intelligence (AI), Natural Language Understanding (NLU), Question Answering, Dialog Management, and Text-to-Speech (TTS). The Machine Learning Platform is at the forefront of this mission with engineering and science innovations, capabilities, services and platforms. This includes aspects of dynamic model building, personalization, language expansion, deep learning platform, data platform and ground truth, and self-serve tools to organize and manage ontologies, catalogs and spoken language understanding capabilities.
We are looking for a strongly technical, customer-focused Principal Technical Program Manager with skills that span science, software engineering, product management and sheer vision. In this role you will:
· Help formulate and communicate strategic direction for the Alexa Machine Learning Platform to deliver unfailingly in the customers interests
· Proactively cultivate fruitful and meaningful partnerships and outcomes with all stakeholders
· Help develop product thinking and metrics in the organization that are meaningful to all stakeholders
· Help nurture a culture of cross-discipline scientific and engineering innovation
· Incubate and help nurture new technical or product programs
· Originate and drive cross-team initiatives focused on increased visibility, communication, collaboration, velocity, engineering excellence, and proactive planning
· Create mechanisms for improving and reporting on organization and program health, effectiveness, efficiency, costs, and ROI
· Coordinate and simplify cross-team efforts for planning, budget, headcount allocation, costs, OP1 and related processes
· Drive solutions from the data – dive deep into experience data to identify problems and push for solutions, writing your own analytic scripts and tools where necessary
· Drive consistent results and customer impact across the scientific and engineering teams.