Offers “Amazon”

Expires soon Amazon

Applied Scientist

  • California (St. Mary's)
  • IT development

Job description

DESCRIPTION

Amazon is looking for creative Applied Scientists to tackle some of the most interesting problems on the leading edge of Machine Learning (ML), Natural Language Processing (NLP), and Information Retrieval (IR) with our Alexa search team. Alexa search is part of our ongoing Alexa Information efforts focused on reinventing information extraction and retrieval for a voice-forward, multi-modal future.

The successful candidate will develop novel ML/NLP/IR/Deep Learning technologies to make Alexa smarter. They will have a true passion for working in a collaborative, cross-functional environment that encourages thinking about optimized solutions to unique problems that do not have yet a known science solution.

If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel algorithms and modeling techniques to leverage and advance the state-of-the-art in technology areas that are found at the intersection of ML, NLP, IR, and Deep Learning. Your work will directly impact Amazon products and services that make use of speech and language technology. You will gain hands on experience with Alexa and large-scale computing resources.

In this role you will:
· Work collaboratively with scientists and developers to design and implement automated, scalable NLP/ML/IR models for accessing and presenting information;
· Drive scalable solutions from the business, to prototyping, production testing and through engineering directly to production;
· Drive best practices on the team, deal with ambiguity and competing objectives, and mentor and guide junior members to achieve their career growth potential.

Desired profile

BASIC QUALIFICATIONS

· PhD in ML, NLP, IR, Computer Science or a related field
· 3+ years of work experience.
· Experience in designing and building large scale ML, NLP, or IR systems.
· Record of publication in peer-reviewed journals and conferences in the field.

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