Machine Learning Engineer, Advertising & Marketing Performance Intelligence

Amazon’s Advertising & Marketing Performance Intelligence (AMPI) team is hiring a Machine Learning Engineer to develop, deploy, and scale production-grade machine learning and GenAI solutions. This onsite role in Seattle focuses on building ML infrastructure and enabling automated decision-making and personalized marketing communications.

Role Responsibilities

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

Required Qualifications

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

Technologies and Tools

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

Location: Seattle, WA (onsite).
Salary: USD 143,700 - 194,400 per year.

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• 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
• Parental leave