A

Amazon

Sells products online and rents cloud computing

Senior Applied Scientist - Multiple Teams

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 5 years of experience building machine learning models for business applications.
  • A PhD, or a Master's degree and at least 6 years of applied research experience.
  • Experience programming in Java, C++, Python, or a related language.
  • Experience with neural deep learning methods and machine learning.

Responsibilities

  • Understand cross-border advertisers' pain points as they scale across marketplaces, and build science-driven solutions that remove barriers and accelerate their growth and success.
  • Build agentic and machine learning systems that autonomously create, structure, and manage ad campaigns on advertisers' behalf, encoding auction and marketplace dynamics such as bidding, budget pacing, and targeting decisions while balancing advertiser return on investment, shopper experience, and marketplace health.
  • Innovate on simpler ways to advertise powered by generative AI, and advance existing autonomous programs such as auto-targeting and global lift-and-shift while proposing and prototyping the next generation of campaign automation.
  • Develop models across the campaign lifecycle, including opportunity discovery, ranking, ad-readiness and demand prediction, and bid and budget optimization, applying classical machine learning or large language model and reasoning methods as appropriate.
  • Define and curate datasets and signals needed to train and evaluate the systems, including advertiser and campaign data, cross-marketplace performance, auction and bid/budget signals, impressions, clicks, conversions, and search-term and keyword performance.
  • Own core parts of the agentic architecture, including planning, tool use and integration such as MCP, reasoning frameworks such as ReAct and CoT/ToT, and model customization; define evaluation and safety methodology so automated decisions are reliable and trustworthy.
  • Write production-quality critical-path code and build core components to take systems from prototype to launch on large-scale pipelines such as Spark/EMR and Airflow, as well as online serving.
  • Mentor scientists and engineers, review designs and experiment plans, and communicate results and tradeoffs clearly to technical and business leaders.

Desired Qualifications

  • Experience with modeling tools such as R, scikit-learn, Spark MLlib, MxNet, TensorFlow, NumPy, and SciPy.
  • Experience with large-scale distributed systems such as Hadoop and Spark.

About the Company

Amazon

Sells products online and rents cloud computing

Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Seattle, WA
Founded
1994

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