Senior Applied Scientist, Advertising Trust

Amazon; San Diego (CA); On-site; USD 150,000 - 260,000; Full time

Job summary

Amazon is seeking a Senior Applied Scientist for its Advertising Trust team in San Diego. The successful candidate will leverage their machine learning expertise to improve ad relevance and compliance while driving the growth of performance advertising products. This role emphasizes collaboration, innovation, and the chance to work at the forefront of advertising technology. Ideal candidates will hold advanced degrees with substantial experience in machine learning and programming across various languages.

Qualifications

• 3+ years building machine learning models for business applications.
• Experience with large scale distributed systems.
• Expertise in visual and textual feature models.

Responsibilities

• Build and develop machine learning models for content understanding.
• Collaborate with engineers to deploy models.
• Develop production level code for ad moderation.

Skills

Machine Learning

Content Understanding

Programming in Python

Programming in Java

Programming in C++

Neural Deep Learning

Education

PhD in related field

Master's degree and 6+ years of applied research experience

Tools

R

Scikit-learn

Tensorflow

NumPy

Spark MLLib

Job description

Senior Applied Scientist, Advertising Trust

Job ID: 3008646 | Amazon.com Services LLC

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.

The ATT team, based in San Diego, is responsible for ensuring that ads are relevant and compliant to policies, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handling billions of requests a day with plans to grow by an order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages.



Key job responsibilities
In this role, you will build and develop ML models to address content understanding problems in Ads. These models will rely on a variety of visual and textual features requiring expertise in both domains. These models need to scale to multiple modalities, languages, and countries. You will collaborate with engineers and other scientists to build, train and deploy these models. As part of these activities, you will develop production level code that enables moderation of millions of ads submitted each day.

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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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.

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.