Sr Applied Scienitst

“Find a coffee shop between here and San Francisco,” “How much longer is Target on main street open?,” “What is the next train to work,” “I need directions to the nearest gas station;” these are some of the utterances answered by the Alexa Local Information team. We enable customers to search for places, products, or services around them, and provide personalized travel, commute and navigation experiences to the places they find.

Our science team works at the intersection of ASR, NLU, Information
Retrieval, Machine Learning and Big Data. We leverage techniques from all these fields to create novel algorithms that advance the state of the art in spoken language understanding and improve search quality for local Points of Interest (POI’s). Our work directly impacts the experience and engagement of customers who rely on Alexa to find relevant locations while in-the-car, on-the-go and at-home.

In this role you will:
- Perform hands-on data analysis and modeling with large data sets to develop insights that increase device usage and customer experience
- Apply Machine Learning and SLU techniques to improve our conversational interfaces and search algorithms
- Run A/B experiments, evaluate the impact of your optimizations and communicate your results to various business stakeholders
- Work closely with product managers and software engineers to design experiments and implement end-to-end solutions
- Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them
- Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
- You will mentor fellow scientists in the team
- Help attract and recruit technical talent

We are open to hiring candidates to work out of one of the following locations:

Sunnyvale, CA, USA

Basic Qualifications

- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred Qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.