As an Applied Scientist in Commercial Electronics (CE) Tech, will be tasked to understand and work with leading edge research to enable the implementation of sophisticated models on big data. As a successful applied scientist in the team, you are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and machine learning algorithms, can multi-task, and can credibly interface between engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.In this role, you will be able to dive deep into data, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI.Key job responsibilities- Design data architectures and machine learning, deep learning, NLP algorithms, Generative AI- Use ML tools to annotate data, design and implement AI workflow and end-to-end pipelines.- Create scalable ML solutions for solving business problems.- Interact with product to understand the business problem, provide solution and insights to solve those problems- Educate engineering teams to understand the science models and machine learning technology- Analyze and extract relevant information from large amounts of historical data - provide hands-on data wrangling expertise- Work closely with Engineering and Product teams to drive model implementations and new algorithms- Design experiments to evaluate the performance of the model- Design and analyze A/B test results to estimate the impact of the model- This position can have periods of up to 5% travelWe are open to hiring candidates to work out of one of the following locations:Seattle, WA, USA- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 1+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience- 1+ years of solving business problems through machine learning, data mining and statistical algorithms experience- 1+ years of programming in Java, C++, Python or related language experience- 1+ years of hands-on predictive modeling and large data analysis experience- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Experience with popular deep learning frameworks such as MxNet and Tensor Flow- Publication on Deep Learning, NLP, Machine Learning conferencesOur 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 $222,200/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.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.