Amazon.com Services LLC
Direct employer career site

Sr. Machine Learning Engineer

Pay
$168,100 – $261,500 per year
Location
Seattle, WA
Listed
2 days ago

About the role

The Ad Response Prediction team builds the machine learning systems that decide which ads are most relevant to shoppers across every Amazon platform and surface worldwide. You'll own the architectural direction of the ML infrastructure behind ad relevance, covering large-scale training systems, real-time inference and the LLM-based architectures that support next-generation GenAI workloads at Amazon Ads scale.

The team sits at the core of how Sponsored Products & Brands (SPB) is using generative AI to change advertising. The models and infrastructure we build directly determine ad relevance across Amazon's entire advertising surface. You'll work closely with applied scientists to take models from training and evaluation through deployment and serving. You'll also shape ML infrastructure practices beyond your immediate team.

Key job responsibilities

  • Lead the development of LLM inference infrastructure for next-generation GenAI workloads at Amazon Ads scale: define the technical strategy, evaluate tradeoffs and deliver production-ready solutions
  • Own the architectural direction of large-scale ML training and real-time inference systems, driving improvements in scalability, automation and efficiency across the organization
  • Partner with applied scientists to design and optimize end-to-end ML pipelines, from model training and evaluation through deployment and serving, so models perform reliably at massive scale
  • Influence technical direction beyond your team by establishing ML infrastructure best practices and contributing to cross-team architectural decisions
  • Make principled tradeoff decisions on complex, ambiguous problems in a fast-moving GenAI space, bringing clarity and delivering results independently
  • Mentor engineers across the team and be the technical resource others seek out for ML infrastructure expertise

Basic Qualifications

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave.

  • USA, CA, Palo Alto - 193,300.00 - 261,500.00 USD annually
  • USA, VA, Arlington - 168,100.00 - 227,400.00 USD annually
  • USA, WA, SEATTLE - 168,100.00 - 227,400.00 USD annually

About the team

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond.

We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.

We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

The Ad Response Prediction team within SPB is at the core of this work. The models and infrastructure we build directly determine ad relevance across Amazon's entire advertising surface. We're a collaborative, high-ownership team that moves fast and builds ML systems that operate at internet scale.

Read the original posting

From Amazon.com Services LLC's careers page, first listed on Rolev.ai on November 7, 2026. Rolev.ai is not the employer.

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Common questions

What is the salary for the Sr. Machine Learning Engineer role at Amazon.com Services LLC?

The Sr. Machine Learning Engineer posting at Amazon.com Services LLC states compensation of $168,100 – $261,500 per year. Final pay may depend on location, experience, and interview evaluation on Amazon.com Services LLC's official career site.

Where is the Sr. Machine Learning Engineer job at Amazon.com Services LLC located?

This Sr. Machine Learning Engineer position at Amazon.com Services LLC is located in Seattle, WA. Always check Amazon.com Services LLC's application page for specific state eligibility or relocation policies.

How do I apply for the Sr. Machine Learning Engineer position at Amazon.com Services LLC?

This listing links directly to Amazon.com Services LLC's application page. You can apply directly on Amazon.com Services LLC's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.