Amazon is hiring: Machine Learning Engineer, Advertising in Live Events in New Y
Amazon, New York, NY, United States, 10261
Description
The Advertising in Live Events (ALE) team is seeking a passionate and innovative Machine Learning Engineer (MLE) to play a crucial role in revolutionizing the live sports advertising experience through advanced ML, Generative AI, and intelligent agents. As our MLE, you will be at the forefront of developing machine learning models, autonomous agents, and generative algorithms that power our world-class live sports ad program. Your work will directly impact millions of viewers, advertisers, and league partners by creating unique, never-before-seen ad experiences across multiple platforms including Prime Video, Twitch, and other first-party streaming apps.
In this role, you will leverage Amazon's vast data resources and state-of-the-art computing infrastructure to develop and optimize AI/ML systems that enhance ad relevance, customization, and impact. Your expertise will be instrumental in bridging the gap between traditional broadcast television advertising and the future of personalized, AI-driven ad experiences in live sports.
Key job responsibilities
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Design and implement advanced ML models and generative AI systems to improve ad targeting, creative generation, placement, and viewer experience in live sports events
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Develop autonomous agents for real-time ad optimization, monitoring, and decision-making during live events
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Lead the integration of Large Language Models (LLMs) for automated content analysis, ad context understanding, and creative optimization
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Create AI-powered systems for dynamic ad personalization and real-time content adaptation
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Collaborate with cross-functional teams to integrate ML/GenAI solutions into existing ad serving, measurement, and campaign management technology stacks
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Develop intelligent agents for automated property management and event monitoring
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Analyze large-scale datasets to derive insights and improve model performance
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Contribute to the technical roadmap for global expansion of our AI-enhanced advertising products
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Mentor junior team members and promote best practices in ML, GenAI, and software development
A day in the life
You will work closely with product teams, partner engineers, and program managers to identify opportunities for AI/ML-driven improvements in our advertising system. You'll develop and deploy intelligent agents that can autonomously monitor live events and make real-time decisions about ad placement and optimization. You'll leverage generative AI to create and test new ad formats and experiences. You'll analyze viewer data, ad performance metrics, and real-time event information to develop models that enhance ad relevance and effectiveness. You'll also participate in cross-team initiatives to expand our AI capabilities to new regions and properties, applying your expertise to solve unique challenges in different markets.
About the team
We are the Advertising in Live Events team, and our mission is to build the most advanced Live Event advertising offering for brands to reach viewers in the most relevant and least disruptive way possible. Through the power of ML, GenAI, and autonomous agents, we aim to bring intelligent, digital advertising capabilities to a traditionally linear advertising space and make advertising in live sports available to all advertisers. Join us in shaping the future of AI-powered sports advertising and be part of a team that's redefining the viewer experience.
Basic Qualifications
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Bachelors or Masters degree in Computer Science, Machine Learning, or a related field
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3+ years of professional experience in machine learning or data science roles
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Strong programming skills in Python, and experience with ML frameworks such as TensorFlow or PyTorch
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Experience in developing and deploying machine learning models in production environments
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Experience with generative AI models and LLMs
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Knowledge of autonomous agents and reinforcement learning
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Proficiency in working with large-scale datasets and distributed computing systems
Preferred Qualifications
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Ph.D. in Machine Learning, Computer Science, or a related field
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Experience with real-time machine learning systems and online learning algorithms
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Experience with transformer architectures and large language models
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Practical experience in developing and deploying autonomous agents
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Familiarity with advertising technology, programmatic advertising, or ad serving systems
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Knowledge of cloud computing platforms, preferably AWS
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Publications in top-tier ML/AI conferences or journals
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Experience with multi-agent systems and agent-based architectures
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.