Machine Learning Engineer, Advertising & Marketing Performance Intelligence
Posted Updated
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.
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.