Software Dev Engineer, Sponsored Products and Brands Ads Response Predictio at Amazon SZ South 3 GmbH

Palo Alto, California, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Jan, 26

Salary

223600.0

Posted On

25 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Software Development, Generative AI, Data Mining, Information Retrieval, Statistics, Natural Language Processing, Model Deployment, Performance Analysis, Collaboration, Scalability, Automation, Efficiency, Code Reviews, Source Control Management, Build Processes

Industry

Software Development

Description

About Sponsored Products and Brands The Sponsored Products and Brands (SPB) 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. Key job responsibilities As a Software Development Engineer in Machine Learning, you will: * Enhance the scalability, automation, and efficiency of large-scale training and real-time inference systems. * Pioneer the development of LLM inference infrastructure to support next-generation GenAI workloads at Amazon Ads scale. * Partner with Applied Scientists to productionize and scale end-to-end generative AI solutions, optimizing model performance and inference infrastructure. About the team SPB Ad Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are looking for a talented Software Engineer with a strong background in machine learning engineering to join our team and help us grow the business. In this role, you will partner with a team of engineers and scientists to build advanced machine learning models and infrastructure, from training to inference, including emerging LLM-based systems, that deliver highly relevant ads to shoppers across all Amazon platforms and surfaces worldwide. Basic Qualifications: - 1+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language Preferred Qualifications: - 2+ years of non-internship professional software development experience - Bachelor's degree in computer science or equivalent - Experience in machine learning, data mining, information retrieval, statistics or natural language processing - Demonstrated track record of successfully implementing GenAI solutions in production environments, including model deployment, monitoring, and continuous improvement. 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 [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 [https://www.aboutamazon.com/workplace/employee-benefits]. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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Responsibilities

As a Software Development Engineer in Machine Learning, you will enhance the scalability, automation, and efficiency of large-scale training and real-time inference systems. You will also partner with Applied Scientists to productionize and scale end-to-end generative AI solutions.