Software Engineer - Ai/ml, Ads Marketing - Advertiser Growth Technology Team

Amazon Amazon · Big Tech · NY +1 · Software Development

Software Engineer role on the Ads Marketing team, focusing on building an AI-powered marketing intelligence engine (MCC) that uses autonomous AI agents for campaign management. The role involves designing, developing, and deploying production-grade ML systems, owning AI/ML pipelines, and collaborating with Applied Scientists. The system aims to automate repetitive tasks and improve campaign execution time.

What you'd actually do

  1. Design, develop, and deploy production-grade engineering and machine learning systems that deliver measurable customer impact at scale.
  2. Write clean, efficient, and well-tested code while collaborating with cross-functional teams to deliver scalable systems.
  3. Own end-to-end AI/ML pipelines including data processing, optimization, and inference infrastructure.
  4. Lead technical design discussions, mentor engineers, and drive architectural decisions for AI/ML solutions.
  5. Collaborate with Applied Scientists to productionize research innovations while ensuring system reliability, performance, and cost efficiency.

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • 2+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
  • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
  • Experience programming with at least one software programming language
  • Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
  • Strong AI/ML interests and qualifications in Artificial Intelligence, machine learning, and/or Generative AI, such as computer vision, deep learning models

Nice to have

  • Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience building complex software systems that have been successfully delivered to customers

What the JD emphasized

  • production-grade engineering and machine learning systems
  • end-to-end AI/ML pipelines
  • AI/ML solutions
  • AI/ML technologies

Other signals

  • AI-powered marketing intelligence engine
  • autonomous AI agents
  • orchestration
  • production-grade engineering and machine learning systems
  • end-to-end AI/ML pipelines