Skip to main content

Sr. Principal Applied Scientist, Sponsored Products

Job ID: 2768002 | Amazon.com Services LLC

DESCRIPTION

The Sponsored Products (SP) team is looking for a Sr. Principal Scientist to help our millions of shoppers intuitively navigate our vast inventory by harnessing the power of GenAI models.
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, SP helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's 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!

As a Senior Principal Scientist in Sponsored Products, you will have deep subject matter expertise in the area of large language models and generative AI across various modalities. You will work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables. You will invent new product experiences that enable our shoppers to easily navigate our vast inventory either via search queries, multi-turn conversations, or other modes of input. You will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production in the retrieval and relevance ranking models used in Sponsored Products. You will stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. You will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of of applied scientists, and engineers. Finally, you will work with academic partners to support our in-house talent with direct access to cutting edge research and mentoring.

BASIC QUALIFICATIONS

Graduate degree in Computer science/Math or related field.

Experience in building complex, real-time systems involving AI, ML, and NLP with successful delivery to customers.

Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements.
Ability to take a project from requirements gathering and design to actual product launch
Computer Science fundamentals in data structures, algorithm design and complexity analysis.

Ability to develop machine learning platform strategy in the domain of recommender systems.

Exceptional customer understanding skills including the ability to discover the true challenges to efficient product discovery, and experience in leading science efforts to meet aggressive timelines with optimal solutions.

Demonstrated track record of peer-reviewed scientific publications that advance state-of-the art for applied science.

PREFERRED QUALIFICATIONS

15+ years of relevant, broad research experience after PhD degree or equivalent.

Deep expertise in Machine Learning as applied to large-scale generative models
Proficiency in programming for algorithm and code reviews.

Strong core competency in mathematics and statistics.

Track record of successful projects in algorithm design and product development.

Publications at top-tier peer-reviewed conferences or journals.

Strong prior experience with mentorship and/or management of senior scientists and engineers.
Thinks strategically, but stays on top of tactical execution.

Exhibits excellent business judgment; balances business, product, and technology very well.

Effective verbal and written communication skills with non-technical and technical audiences.
Experience working with real-world data sets and building scalable models from big data.


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.

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 compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $240,100/year in our lowest geographic market up to $350,000/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.