Machine Learning Engineer, Advertising & Marketing Intelligence

On Amazon’s Advertising & Marketing Performance Intelligence (AMPI) team, you will design, deploy, and scale production-grade machine learning and GenAI solutions that support automated decision-making and personalized marketing communications. This onsite role in Seattle pairs ML engineering with infrastructure work, spanning large-scale training systems, monitoring, and cost-aware AI/ML operations.

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

• 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.

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

• Location: Seattle, WA (onsite)
• Salary: USD 143, per year

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, with 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

• 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+ year building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search.