Description

The Amazon Search team creates powerful, customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day.

We’re seeking an Applied Scientist with a deep expertise in matching and ranking systems. Your responsibilities will include everything from developing and prototyping innovative retrieval systems with NLP and Transformer, query planning, deep learning to operating and optimizing a scalable distributed inference solutions in a production environment. We are looking for innovators who can contribute to advancing search technology on what’s scientifically possible while remaining committed to creating world-class products.

Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), Earth's most customer-centric company one of the world's leading internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California.

Key job responsibilities

• Act as the technical leader in Machine Learning, Information Retrieval, and drive full life-cycle Machine Learning projects.

• Lead technical efforts within this team and collaboration with other science teams.

• Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.

• Run A/B experiments, gather data, and perform statistical tests.

• Establish scalable, efficient, automated processes for large-scale data mining, machine-learning model development, model validation and serving.

• Work closely with junior scientists, software engineers and product managers to assist in productizing your ML models.

• Establish new research initiatives to shape our long-term science vision.

• Act as a mentor to other Scientists on the team.

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

Palo Alto, CA, USA

Basic Qualifications

• PhD in CS, Statistics, or a related discipline

• 8+ years of experience in industry, consulting, government, or academic research.

• Effective verbal and written communications skills

• Track record of thought leadership and contributions that have advanced the field.

• Strong skills in collaboration and teamwork

• Strong record of delivery in industry and academic contexts using Machine Learning

Preferred Qualifications

• Published research work in academic conferences or industry circles.

• Technical leadership in large-scale machine learning, deep learning, and large language models for recommendation systems

• Thinks strategically and staying on top of tactical execution.

• Exhibits excellent business judgment and understanding of science, engineering, and business trade-offs.

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 $159,100/year in our lowest geographic market up to $309,400/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.