Amazon is looking for a Senior Applied Scientist to join an exciting new project team working to build a completely new best in class consumer product. We require deep expertise with Natural Language Understanding (NLU) in order to help us derive a machine-understandable representation of a conversation in both real-time and once the conversation is complete. To achieve these goals, we are tackling challenging problems related to deep semantic parsing and coreference resolution using a combination of techniques, including deep learning approaches such as attention-based models, LSTMs and RNNs.
Who we are
We are a small team building new voice-forward products and experiences that delight our customers. Think of a startup within Amazon; with the ability to solve challenging problems which leverage the breadth of voice technology within Amazon. Our mission is to push the boundaries in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), in order to provide the best-possible experience for our customers.
Who you are
You are an expert in a wide variety of NLU/NLP techniques with a proven track record working with state-of-the-art approaches and guiding small teams of scientists. You are passionate about the quality your work, and strive to share your results in publications. You are comfortable working with engineers to build end-to-end solutions.
What you'll be doing
Coding in the language of your choice.
Defining strategies for data annotation, and helping to guide the annotation process.
Building models that leverage conversational context to produce summaries.
Building models that produce a deep semantic representation of conversational dialogue turns.
Mentoring junior scientists and software developers.
Authoring and publishing papers to document your results.
Actively maintaining and improving your knowledge by reviewing papers.
Leading reading groups to help ensure that our group is aware of the most recent ML and deep-learning techniques.
Maintaining a high quality bar for production models.
Working with software engineers to identify great features that will the product delight customers.
Contributing with technical guidance on software design, architecture, patterns and practices.
Build relationships with your customers, partner teams and the engineers on your team.
Believe there are generally multiple ways to solve a technical problem, each with different trade-offs. You don't typically think in terms of the "right" or "wrong" way to do something.
Approach projects, tasks, and unknowns with curiosity, and enjoy sharing what you know and what you learn with the people around you.
Are able to put yourself into your customer's shoes. You frequently immerse yourself in the customer experience to understand how you can better serve them.