Amazon.com Services LLC
Advertising
MachineLearningEngineer,AdResponsePrediction
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Machine Learning Engineer, Ad Response Prediction at Amazon.com Services LLC. Skills: Machine Learning, Software Development, AI, E-commerce. Design scalable machine-learning pipelines. Code scalable machine-learning pipelines”
What You'll Achieve.
Deliver highly relevant ads; Improve customer search experience; Improve customer detail page experiences; Deliver amazing products
Industry & Context.
Solve complex challenges; Problem solving; Root cause analysis
What They're Looking For.
Must Have
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field, 3+ years of non-internship professional software development experience, 3+ years of full software development life cycle experience, 2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience, Knowledge of machine learning model architecture and inference
Nice to Have
Knowledge of Machine Learning and LLM fundamentals, Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT, 1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience, Demonstrated track record of innovative AI solution development
What You'll Do.
Design scalable machine-learning pipelines
Code scalable machine-learning pipelines
Troubleshoot scalable machine-learning pipelines
Support scalable machine-learning pipelines
Design online serving systems
Code online serving systems
Troubleshoot online serving systems
Support online serving systems
Optimize performance of machine-learning models
Optimize performance of machine-learning infrastructure
Implement end-to-end solutions
Drive technical direction of offerings
Drive technical direction of solutions
Assess system performance
Build engineering team
Grow engineering team
Work with business partners
Maintain relationships
How You'll Work.
Team & Collaboration
Applied scientists; Product managers; Other engineers; Partner disciplines; User Experience; QA; Engineering leaders
Process & Methodology
Project management
Full Job Description
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. Our systems and algorithms operate on one of the world's largest product catalogs, matching shoppers with advertised products with a high relevance bar and strict latency constraints. We work hand-in-hand with Machine Learning and NLP research scientists to come up with novel solutions that deliver highly relevant ads. We consistently strive to improve the customer search and detail page experiences. You will drive appropriate technology choices for the business, lead the way for continuous innovation, and shape the future of e-commerce. This is an opportunity to make a significant impact on the future of the Amazon vision. As a Machine Learning Engineer at Amazon, you will drive the technical direction of our offerings and solutions, working with many different technologies across the sponsored products organization. You will design, code, troubleshoot, and support scalable machine-learning pipelines and online serving systems. You will work closely with applied scientists to optimize the performance of machine-learning models and infrastructure, and implement end-to
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