- 10+ years of applied ML experience in building complex, real-time systems involving AI, ML, and NLP.
- Hands-on experience with designing and prototyping AI solutions for real world applications.
- Research publications or patents in generative AI technologies.
- Experience with natural language processing and generative model architectures.
- Background in advertising technology or e-commerce platforms.
- Demonstrated track record of innovative AI solution development.
- Experience with advertising systems and applications.
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.
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, CA, Palo Alto - 228,700.00 - 309,400.00 USD annually
USA, NY, New York - 218,800.00 - 295,900.00 USD annually
USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually
The Principal Applied Scientist in Performance Measurement in the Measurement, Ad Tech, and Data Science (MADS) team leads the technical vision and execution for Amazon Advertising's performance measurement. Our measurement products and tools help customers understand the holistic impact of their spend on Amazon Ads and optimize their portfolios. This is a complex, multi-disciplinary scientific space spanning machine learning, causal inference, statistics and experimentation, natural language processing, and generative AI. As a GenAI-first organization, we build foundational and agentic models that power advertiser use cases across Ads, while empowering our Applied Scientists to directly build and ship products. You will guide a team of scientists with expertise across different domains to come together and innovate on some of the hardest problems in advertising, made more challenging by evolving privacy regulations and technological changes. In measuring the comprehensive impact of advertising, key challenges you will tackle include capturing impact: 1) both for identified and increasing unidentified web traffic in light of an evolving global privacy landscape; 2) for outcomes across retailers, including both within and beyond Amazon; and 3) for both short- and long-term impacts of advertising.
The ideal candidate will have deep expertise in ad serving, measurement, and application of advanced machine learning and innovate on measurement solutions that comply with complex privacy policies and regulatory requirements maintaining Amazon Advertising’s competitive edge.
Key job responsibilities
Key job responsibilities include:
* Driving the scientific vision of the teams in your organization and you advise and influence its technical leadership on performance measurement models and products.
* Identifying, tackling, and proposing innovative solutions to intrinsically hard, previously unsolved problems. You solve problems pragmatically, applying judgment and experience to balance trade-offs between competing interests.
* Bringing clarity to complex problems, probe assumptions, illuminate pitfalls, foster shared understanding, and guide towards effective solutions.
* Serving and being recognized by internal and external peers as a thought leader in modeled measurement in Ads. You will engage routinely with the broader scientific community, e.g. as a reviewer, program committee member, workshop organizer, or chair at peer-reviewed internal/external conferences.
* Leading by example, with your papers, analyses, and code setting the standard in your organization for scientific engineering excellence.
* Leading science and design reviews, aligning teams across your organization around coherent algorithmic strategies.
* Influencing your team’s science and business strategy by driving one or more team roadmaps contributing to the organization’s roadmap and taking responsibility for some organizational goals. You drive multiple new product features from inception to production launch.
* Guiding the career development of others, actively mentoring and educating the larger applied science community on trends, technologies, and best practices. You drive the documentation of scientific innovation. You attract bar-raising talent from academia and industry.
* Staying abreast of academic and industry trends, knowing the state of the art, and building on top of existing solutions instead of reinventing when possible
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