3 Sr. Applied Scientist, Fire TV Science Jobs in Sunnyvale, CA
Amazon is Hiring a Sr. Applied Scientist, Fire TV Science Near Sunnyvale, CA
DESCRIPTION
Help re-invent how millions of people watch TV! Fire TV remains the #1 best-selling streaming media player in the US. Our goal is to be the global leader in delivering entertainment inside and outside the home, with the broadest selection of content, devices and experiences for customers.
Our science team works at the intersection of Recommender Systems, Information Retrieval, Machine Learning and Natural Language Understanding. We leverage techniques from all these fields to create novel algorithms that allow our customers to engage with the right content at the right time. Our work directly contributes to making our devices delightful to use and indispensable for the household.
Key job responsibilities
- Drive new initiatives applying Machine Learning techniques to improve our recommendation, search and entity matching algorithms
- Perform hands-on data analysis and modeling with large data sets to develop insights that increase device usage and customer experience
- Design and 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
- Help attract and recruit technical talent; mentor junior scientists
We are open to hiring candidates to work out of one of the following locations:
Sunnyvale, CA, USA
BASIC QUALIFICATIONS
- PhD, or Master's degree and 6 years of applied research experience
- 3 years of building machine learning models for business application experience
- Experience programming in Java, C , Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 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.
- Experience with Deep Learning for search and recommendation systems
- Experience with NLP and LLM algorithms and tools a plus
- Experience performing and interpreting A/B experiments
- Excellent verbal/written communication skills, including an ability to effectively collaborate with research and technical teams
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.
Job Summary
Full Time
Transportation
$118k-151k (estimate)
02/08/2024
06/01/2024
RANDALLSTOWN, MD
25 - 50
2018
$50M - $200M
Transportation
