Machine Learning Engineer, Advertising & Marketing Performance Intelligence

Join Amazon’s Advertising & Marketing Performance Intelligence (AMPI) team in Seattle, WA (onsite) to build and scale production machine learning and GenAI solutions. This role focuses on developing the ML infrastructure that powers automated decision-making and personalized marketing communications, with an emphasis on efficient training workflows, reliable deployments, and cost-conscious AWS AI/ML execution.

What you’ll work on

• Work with Data and Applied Scientists to process structured and unstructured inputs, scaling ML and LLM infrastructure while optimizing infra costs, GPU utilization, memory management, and production training workflows (including techniques such as offloading optimizer states and massive parallelization).
• Create reusable technical assets that help accelerate adoption of ML, Optimization, and GenAI across multiple science initiatives.
• Design and maintain production-grade large-scale distributed training systems that support ML, Causal, GenAI, and multi-modal foundation models.
• Optimize AWS AI/ML infrastructure costs and improve efficiency across training, including latency and costs, and support fine-tuning on massive datasets.
• Build monitoring and debugging tools to improve reliability and performance of training workflows, support LLM pilots, and surface system issues.
• Collaborate with Engineers, Data, and Applied Scientists to explore design options, prototype new GenAI and ML models, evaluate technical feasibility, and resolve complex problems.

Requirements

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture experience (design patterns, reliability, and scaling) for new and existing systems
• Experience programming with at least one software programming language
• Experience in machine learning, data mining, information retrieval, statistics, or natural language processing

Tech you may work with

• Machine Learning, large language models (LLMs), large quantitative models (LQMs), and AI/ML workflows
• AWS Bedrock, Agentic AI (RAG, agentic architectures, vector databases), and Amazon Q
• SageMaker, containerized deployments, Hugging Face, LangChain, and Guardrail implementations
• Foundational models such as Qwen, Anthropic’s Claude, Mistral, and RCTs

Preferred qualifications

• 3+ years of full software development life cycle experience including coding standards, code reviews, source control management, build processes, testing, and operations
• 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

Compensation and benefits

Salary: USD 143,700 - 194,400 per yearly.

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with options for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, and Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave