Machine Learning Engineer II, Sponsored Products Search Sourcing, Amazon Advertising
Posted 1 day ago
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The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. 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.
We are looking for a Machine Learning Engineer II who can drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of ad serving on Amazon search. You will build services to handle billions of requests per day, while maintaining response latency in milliseconds and meeting strict SLA requirements. It is quite routine for our systems to operate on massive datasets using distributed frameworks. You will design and code, troubleshoot, and support high volume and low latency distributed systems. The solutions you create would ensure relevant ads are served to Amazon's customers. You will directly impact our customers’ shopping experience while helping our sellers get the maximum ROI from advertising on Amazon. This role will provide exposure to innovations in product search, information retrieval, natural language processing (NLP), LLM training, deep learning, and image processing. In addition to being a strongly motivated IC, you will also be responsible for mentoring junior engineers and guiding them to deliver high impacting products and services for Amazon customers and sellers.
Key job responsibilities
Job Responsibilities:
• Drive the direction of our technical solutions, and work on many different technologies such as deep learning, AWS, Auto ML, real-time ML serving systems.
• Design, develop, and production software to support scalable offline machine-learning pipelines and online serving components.
• Work closely with applied scientists to optimize the performance of machine-learning models, improve the team’s machine learning productivity, and advance the technical foundation to empower our science innovation. What you create is also what you own.
We are looking for a Machine Learning Engineer II who can drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of ad serving on Amazon search. You will build services to handle billions of requests per day, while maintaining response latency in milliseconds and meeting strict SLA requirements. It is quite routine for our systems to operate on massive datasets using distributed frameworks. You will design and code, troubleshoot, and support high volume and low latency distributed systems. The solutions you create would ensure relevant ads are served to Amazon's customers. You will directly impact our customers’ shopping experience while helping our sellers get the maximum ROI from advertising on Amazon. This role will provide exposure to innovations in product search, information retrieval, natural language processing (NLP), LLM training, deep learning, and image processing. In addition to being a strongly motivated IC, you will also be responsible for mentoring junior engineers and guiding them to deliver high impacting products and services for Amazon customers and sellers.
Key job responsibilities
Job Responsibilities:
• Drive the direction of our technical solutions, and work on many different technologies such as deep learning, AWS, Auto ML, real-time ML serving systems.
• Design, develop, and production software to support scalable offline machine-learning pipelines and online serving components.
• Work closely with applied scientists to optimize the performance of machine-learning models, improve the team’s machine learning productivity, and advance the technical foundation to empower our science innovation. What you create is also what you own.
Amazon
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