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In Amazon Advertising, we apply Machine Learning at massive scale to optimize programmatic advertising performance. The Demand Tech team owns response prediction and incrementality models that power bid optimization across Amazon DSP and Sponsored Display - determining how billions of ad impressions are valued and served daily across Amazon-owned properties, the open internet, and third-party exchanges.
We are looking for a talented Senior Applied Scientist to join our team of scientists and engineers working on high-impact prediction systems that directly drive advertiser KPIs (CPA, ROAS, incrementality) across endemic and non-endemic programmatic advertising.
What you will do:
Own end-to-end response prediction - design and improve deep learning models for multi-task prediction (click, conversion, page view, incrementality) serving at inference latencies under 10ms at millions of TPS
Build and iterate on calibration mechanisms that keep prediction accuracy stable across rapidly shifting supply distributions
Integrate novel signals (OpenRTB features, customer behavioral sequences, supply quality feeds) into production models to improve optimization quality
Run online A/B experiments at scale, analyze results with statistical rigor, and translate offline gains into measurable business impact
Collaborate closely with engineers on model serving infrastructure (SageMaker, GPU inference, real-time feature stores) to deploy models efficiently at scale
Mentor scientists on the team and contribute to the broader Amazon ML science community through papers, conferences, and internal deep dives
What makes this role unique:
Direct business impact: Your models determine bid prices for billions of daily ad impressions - a 1% prediction improvement translates to tens of millions in advertiser value
Technical depth at scale: Multi-task deep learning architectures serving real-time inference across multiple global regions under strict latency constraints
Diverse problem space: From signal-sparse open internet prediction to calibration under distribution shift, from incrementality measurement to cost-efficient GPU inference
Autonomy and ownership: End-to-end ownership from problem framing through research, experimentation, production deployment, and business metric monitoring
Impact and career growth:
Amazon is investing heavily in building a world-class advertising business. Your work directly influences how Amazon's advertising products optimize campaign performance for advertisers worldwide. You will work with a highly motivated, collaborative team with a broad mandate to experiment and innovate. You will have opportunities to present to senior leadership, define long-term science vision, attend external conferences (NeurIPS, KDD, ICML), and shape the direction of ML-driven advertising at Amazon.
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.
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 - 192,200.00 - 260,000.00 USD annually
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually