Sr. Machine Learning Engineer

Lead the ML infrastructure that powers ad relevance for Amazon Ads, spanning large-scale training, real-time inference, and LLM-based GenAI workloads.

Responsibilities

• Drive the development of LLM inference infrastructure for next-generation GenAI workloads at Amazon Ads scale, including technical strategy, evaluating tradeoffs, and delivering production-ready solutions
• Own architectural direction for large-scale ML training and real-time inference systems, improving scalability, automation, and efficiency across the organization
• Collaborate with applied scientists to design and optimize end-to-end ML pipelines from model training and evaluation through deployment and serving
• Set ML infrastructure best practices and contribute to cross-team architectural decisions beyond your immediate team
• Make principled tradeoff decisions in complex, ambiguous problems within a fast-moving GenAI environment, delivering results independently
• Mentor engineers on the team and serve as a technical resource for ML infrastructure expertise

Requirements

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

About the team

• Sponsored Products and Brands (SPB) at Amazon Ads is using generative AI to reshape how customers discover products and engage with brands across Amazon.com and beyond
• The Ad Response Prediction team builds the ML systems that decide which ads are most relevant to shoppers across every Amazon platform
• Models and infrastructure built by this team directly determine ad relevance across Amazon’s advertising surface
• Work includes large-scale training systems, real-time inference, and LLM-based architectures that support next-generation GenAI workloads at Amazon Ads scale
• High-ownership, collaborative team environment operating at internet scale

Job duties (Los Angeles County applicants)

• Work safely and cooperatively with employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions
• Communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service
• Follow all federal, state, and local laws and Company policies
• Criminal history may have a direct, adverse, and negative relationship with some material job duties, including adherence to company policies, judgment, stress management, safe and respectful work, trustworthiness, professionalism, and safeguarding business operations and reputation
• Pursuant to the Los Angeles County Fair Chance Ordinance, qualified applicants with arrest and conviction records will be considered

Inclusive culture

• If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, visit https://amazon.jobs/content/en/how-we-hire/accommodations
• If your country or region is not listed, contact your Recruiting Partner

Compensation

• Base salary (USA, WA, SEATTLE): USD 168,100 - 227,400 per year
• Final compensation determined based on experience, qualifications, and location

Location: Seattle, WA (onsite)

Experience level: Sr. Machine Learning Engineer (5+ years)

Salary range: USD 168,100 - 227,400 per yearly

Education: Bachelor’s degree in computer science or equivalent

Benefits

• 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