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Job Description

The Advertising & Marketing Performance Intelligence (AMPI) team is seeking passionate and talented MLE to join us. Team is on a mission to
create cohesive, relevant, and truly helpful marketing experiences for every advertiser through automated processes and intelligence that enable scaled personalization. Our team is responsible for defining and publishing automated marketing communications leveraging Machine Learning, large language models (LLMs), large quantitative models (LQMs), and specialized agents using AI/ML workflows.

We are looking for a Machine Learning Engineer (MLE) to develop, deploy and scale robust ML and GenAI solutions in production environment. You will own building ML Infra for production models and feed AI/ML outputs to systems and services . In this role you will closely partner with Applied Scientists, Data Engineers,Product Managers, Software engineers to deliver and implement automated decision-making algorithms. This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping/simulation, to implementation by working closely with colleagues in engineering, science, product management, marketing business operations and finance.

Key job responsibilities
- Collaborate with Data and Applied Scientists to process structured/unstructured data inputs, scale ML and LLM infra while optimizing Infra costs, GPU utilization, memory management, and the training workflows (like offloading optimizer states, massive parallelization, etc) for the production environments.

- Create and deliver reusable technical assets that help to accelerate the adoption of ML, Optimization and GenAI across different science initiatives

- Design and maintain production grade large-scale distributed training systems to support ML, Causal, GenAI and multi-modal foundation models.

- Optimize AWS AI/ML infra costs, GPU utilization for efficient model training, latency, costs and fine-tuning on massive datasets.

- Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows, support piloting the LLMs and identify the related issues in the system.

- Collaborate with Engineers, Data and Applied Scientists to investigate design approaches, prototype new GenAI and ML models, evaluate technical feasibility, identify and solve complex problems.



A day in the life
As a member of our team, you'll work on projects that directly impact millions of Amazon advertisers and Marketers across the globe . This role will provide exposure to state-of-the-art innovations in Big Data, AI/ML systems and help Ads Marketing automate advertiser communications with personalized and relevant content and Measure/Calibrate Marketing effectiveness using RCTs. Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Agentic AI (RAG, Agentic architectures, vector databases), Amazon Q, SageMaker, Containerized deployments, Hugging Face/LangChain, Guardrail implementations and Foundational Models such as Qwen, Anthropic’s Claude / Mistral, among others.

Basic qualifications

- 3+ years of non-internship professional software development 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
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Preferred qualifications

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- 1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, WA, SEATTLE - 143,700.00 - 194,400.00 USD annually
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  • Role Machine Learning Engineer, Advertising & Marketing Performance Intelligence
  • Experience 3-4 years
  • Education Bachelor Degree
  • Work type On-site
  • Location United States
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Amazon
Consumer Apps & Media · 500+ Members · Seattle, WA, United States

Amazon operates a broad portfolio spanning online retail, third-party marketplaces, logistics, cloud computing, advertising, devices, entertainment, and subscription services. Its consumer businesses include Amazon stores and Prime, while Amazon Web Services provides cloud infrastructure, databases, analytics, and AI services. The company also develops products such as Alexa and Kindle, produces and distributes media, and runs fulfillment and delivery networks. Amazon serves consumers, sellers, developers, enterprises, creators, and public-sector customers through interconnected commerce and technology platforms.

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Job Overview
Eligibility
United States Right to work in the United States required.
Workplace
On-site
Job Posted:
1 week ago
Job Type
Full Time
Education
Bachelor Degree
Experience
3-4 years

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