DescriptionAs a Senior Applied Scientist at Amazon, you will be at the forefront of a pioneering initiative to revolutionize customer experiences using Large Language Models (LLMs) and recommender systems. Your expertise will drive the personalization of every interaction across Amazon’s vast ecosystem, ensuring that each message and recommendation resonates personally with our customers.Your mission will be to harness the latest in LLM and machine learning innovations to craft recommender systems that are not just smart, but seem intuitively human. This is more than a technical role—it’s a chance to shape the future of e-commerce by making every user feel like Amazon’s most important customer.If you’re a visionary in the field of applied science, passionate about leveraging LLMs to create impactful, individualized user experiences, we want you. Help us set a new standard for personalization at Amazon, where every interaction is a step towards a more personalized future.Key job responsibilities
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 4+ years of applied research experience
Experience programming in Java, C, Python or related language
Experience with neural deep learning methods and machine learning
A day in the lifeYou are an Applied Scientist with an interest in machine learning, data science, search, or recommendation systems. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products. You enjoy working hard, having fun, and making history!About the teamOur team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones.Basic Qualifications
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
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 $150,400/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Full-time- ID: #52462091
- State: Washington Seattle-tacoma 98101 Seattle-tacoma USA
- City: Seattle-tacoma
- Salary: USD TBD TBD
- Showed: 2024-09-06
- Deadline: 2024-11-05
- Category: Et cetera