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Amazon
Seattle, WA
Source: Amazon careers · View original posting
From Amazon's posting. “We” and “our” refer to the employer.
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.
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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