Senior Machine Learning Engineer, Sponsored Products and Brands Relevance

Based in Palo Alto, CA on site, this Senior Machine Learning Engineer role centers on real-time ML serving for Sponsored Products and Brands Relevance. You will help shape technical direction, mentor engineers, and advance ad relevance using deep learning, NLP/LLMs, and distributed systems at Amazon scale. The position offers a compensation range of USD 193,300 to 261,500 per year and a comprehensive benefits package designed to support health, financial security, and work-life balance.

Benefits and culture

• 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

Responsibilities

• Set the technical direction for ML solutions across deep learning, AWS infrastructure, AutoML, and real-time serving systems
• Design, develop, and own scalable offline ML pipelines and online serving components that process billions of requests per day with millisecond latency
• Collaborate closely with applied scientists to optimize model performance, boost ML productivity, and strengthen the technical foundation that powers scientific innovation
• Troubleshoot and support high-volume, low-latency distributed systems, taking ownership of what you build
• Mentor junior engineers to deliver high-impact products and services for Amazon customers and sellers
• Make technology choices that balance innovation velocity with operational excellence and business needs

Qualifications

• 8+ years of non-internship professional software development experience
• 10+ years of programming experience in at least one software language
• 5+ years leading design or architecture of new and existing systems, including design patterns, reliability, and scaling
• Experience as a mentor, tech lead, or leading an engineering team
• Knowledge of machine learning and LLM fundamentals, including transformer architectures, training/inference lifecycles, and optimization techniques
• 5+ years building large-scale ML infrastructure for online recommendation, ads ranking, personalization, or search
• Demonstrated ability to drive technical decisions across teams and deliver end-to-end from design through production deployment

Technologies

• PyTorch
• TensorFlow
• SageMaker
• Triton
• vLLM
• Spark
• AutoML
• AWS