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Amazon · Bellevue, WA

Sr. Machine Learning Engineer, PXT EXR-Ops Tech

US, WA, BellevueSenior individual contributorData & Analytics

Listed on Amazon’s official careers site. Posted September 22, 2026. Check that it is still open and apply there.

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Job description

We are looking for a Senior Machine Learning Engineer who will serve as a technical leader, driving the design and delivery of complex, large-scale ML systems that have significant business impact. In this role, you will define the ML architecture and technical strategy for your team, influence cross-organizational ML platform decisions, and raise the bar for ML engineering excellence. You will build super-intelligent AI systems, lead the development of production-grade AI services including generative AI and LLMs, and mentor a team of ML engineers.

This is a high-impact role requiring deep technical expertise, strong judgment, and the ability to operate in ambiguous problem spaces.

Key job responsibilities

  • Define and drive the ML technical strategy and architecture for your team and adjacent teams
  • Design and lead the implementation of complex, multi-model ML systems at Amazon scale
  • Architect ML platforms and frameworks that enable rapid experimentation and deployment across the organization
  • Lead the design of real-time and batch ML serving infrastructure with high availability and low latency
  • Drive adoption of ML best practices including MLOps, model governance, responsible AI, and cost optimization
  • Evaluate and introduce new ML technologies, frameworks, and methodologies (e.g., foundation models, RAG, fine-tuning, RLHF)
  • Lead cross-functional initiatives spanning science, engineering, product, and business teams
  • Influence org-wide technical decisions through design reviews, architecture reviews, and technical writing (design documents, white papers)
  • Mentor and develop L4 and L5 ML engineers; raise the hiring bar as a bar raiser or interviewer

Drive operational excellence

  • define SLAs, build dashboards, automate incident response, and reduce operational burden

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