Amazon Ads is re-imagining advertising through generative artificial intelligence (AI) technologies. We combine human creativity with AI to transform every aspect of the advertising life cycle, from ad creation and optimization to performance analysis and customer insights. Our solutions help advertisers grow their brands while enabling millions of customers to discover and purchase products through delightful experiences. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground in product and technical innovations. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
Why you’ll love this role:
Amazon is investing heavily in building a world-class advertising business. To meet Advertiser goals, we process over 4 million ad request per second. This team defines and delivers optimization solutions for this enormous volume of traffic filtering unnecessary ad request and processing only whats in-demand and brings value for our Advertisers. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.
You'll work alongside talented engineers, and product leaders in a culture that encourages bias for action, innovation and experimentation, and you will directly influence business strategy through your scientific expertise. What makes this role unique is the combination of scientific rigor with real-world impact. You will re-imagine advertising through the lens of advanced ML while solving problems that balance the needs of advertisers, customers, and Amazon's business objectives.
Your impact and career growth:
Amazon Ads is investing heavily in AI and ML capabilities, creating opportunities for scientists to innovate and make their marks. You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.
Learn more about Amazon Ads:
https://advertising.amazon.com/
Key job responsibilities
As a Senior Applied Scientist in Amazon Ads, you will:
- Conduct hands-on data analysis, build large-scale machine-learning models and pipelines
- Build ML models, perform proof-of-concept, experiment, optimize, and deploy your models into production, working closely with
cross-functional teams including engineers, product managers, and other scientists
- Design and run A/B experiments to validate hypotheses, gather insights from large-scale data analysis, and measure business impact.
- Research and implement ML approaches, including applications of generative AI and large language models.
- Drive end-to-end optimization projects that tackle ambiguous problems at massive scale, often working with petabytes of data.
- Provide technical leadership, research new
machine learning approaches to drive continued scientific innovation
- Build supply optimization 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.
- Develop scalable, efficient processes for model development, validation, and deployment that optimize traffic monetization while maintaining customer experience
- 5+ 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
- 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.
Pursuant to the San Francisco 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.