Sr. Applied Scientist Speech & NLU, Alexa Experience Amazon
Seattle, WA

Job Description

The Alexa Experience organization owns a number of programs and domains which drive high customer engagement and feature discovery, maintains customer trust, understands customers' feedback, develops new features that provide utility value for customers with special needs, and develops locally relevant experiences. The Alexa Experience Science team applies machine learning and natural language understanding algorithms to improve these programs and the functionality of domains such as News ("Alexa, What's the news?"), Feedback ("Alexa, that was wrong!"), UnSpun ("Alexa, what's your favorite color?"), and to advance Alexa's ability to handle more ambiguous utterances.

We're looking for passionate, talented, and inventive Senior Scientist to help build industry-leading ML technologies that help provide the best-possible experience for our customers. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to develop new features, predict key user behaviors and deliver automated decisions, both offline and in real time.

What You Will Do

* Step in as an experienced member of an applied data science / machine learning research team, establish technical credibility quickly, and help recruit elite machine learning practitioners.
* Contribute to setting up the research vision for the team, and develop and execute on a roadmap that addresses the major questions faced by the domains we serve.
* Raise the bar for research quality and impact. Stay up to date on research results both within and complementary to the Alexa technology space and helping both your team and the larger org utilize tried patterns and state of the art results to work smarter and faster.
* See it through - don't stop at delivering a report or a model, use your work to influence and create durable change in how leaders at Alexa think about problems.
* Solve problems durably - design processes, tools, and programs that solve entire categories of problems without you or your team's direct intervention.
* Hands-on practitioner - You yourself are actively involved in performing data analysis, A/B experimentation and modeling with large data sets to develop insights that increase device usage and customer experience
* Work closely with product managers and software engineers to design experiments and implement end-to-end solutions. Communicate the results of your optimizations to various business stakeholders
* Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
* Develop the skills of junior members through mentorship and training.