Applied Scientist, CreativeX

Full Job Description

Amazon Advertising is one of Amazon's fastest growing businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Creative X team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related. As an Applied Scientist you will be part of a close-knit team of other applied scientists, engineers and product managers who are highly collaborative and at the top of their respective fields.

We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the interface of how users can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring innovative research to raise the bar within the team.

You will:

• Drive the invention and development of novel methods for the use of Generative AI in ads
• Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity.
• Build interface-oriented systems that use Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Run A/B experiments, gather data, and perform statistical analysis.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
• Mentor and help recruit Applied Scientists to the team.
• Present results and explain methods to senior leadership.
• Willingness to publish research at internal and external top scientific venues.
• Write and pursue IP submissions.

Key job responsibilities This role is focused on developing Machine Learning and Generative AI methods to augment generative imagery and videos. You will develop new paradigms that will impact how users can engage and benefit from GenAI and that are at the core of advertising-facing tools that we are launching. You will also work on development of ML and GenAI models. You will conduct literature reviews to stay on the top of the field. You will regularly engage with product managers, who will partner with you to productize your work.

About the team

Basic Qualifications

• PhD, or a Master's degree and experience in CS, CE, ML or related field
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience in building machine learning models for business application
• Experience with experimental design
• Experience with programming languages such as Python, Java, C++
• Experience with researching, publishing and or developing human-in-the-loop systems

Preferred Qualifications

• Experience using Unix/Linux
• Experience in professional software development

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

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 172,400.00 - 223,400.00 USD annually USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually

PhD, or a Master's degree and experience in CS, CE, ML or related field Experience in patents or publications at top-tier peer-reviewed conferences or journals Experience programming in Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Experience in building machine learning models for business application Experience with experimental design Experience with programming languages such as Python, Java, C++ Experience with researching, publishing and or developing human-in-the-loop systems