Machine Learning Engineer, Advertising & Marketing Performance Intelligence

DataJobs; Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon’s Advertising & Marketing Performance Intelligence (AMPI) team seeks an ML engineer to design, deploy, and scale production-grade ML and GenAI solutions for automated decision-making and personalized marketing communications. This onsite Seattle role combines ML engineering with infrastructure work on large training systems.

You’ll optimize AWS AI/ML infrastructure, build reusable assets, and collaborate with data scientists to improve training workflows, monitoring, and reliability on

Qualifications

• 3+ years of software development experience (non-internship).
• Bachelor’s degree in computer science or equivalent.
• 1+ year building ML infrastructure for online systems.

Responsibilities

• Process data with scientists to scale ML and GenAI workloads while optimizing costs.
• Build reusable assets for ML, optimization, and GenAI adoption.
• Design production-grade distributed training systems for ML workloads.
• Optimize AWS AI/ML infrastructure for training efficiency and GPU use.
• Create monitoring and debugging tooling for training reliability.
• Collaborate to evaluate designs and prototype new GenAI models.

Skills

Software development

System design

ML basics

Education

Bachelor's degree in Computer Science

Tools

AWS Bedrock

SageMaker

Hugging Face

LangChain

Amazon Q

Job description

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.

What you’ll do

• 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.

Basic 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 you may work with

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

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, 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

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