Design agentic AI systems for Alexa Daily Essentials, applying reinforcement learning and evaluation science to customer-facing features at scale. Work across prototyping and production deployment.

As an Applied Scientist II, you will create systems that reason, plan, and act over complex data. You will apply reinforcement learning, retrieval-augmented generation, and rigorous evaluation methods. Your work will prototype AI-powered features, validate architecture decisions, and influence product roadmaps through experiments and measured quality. You will collaborate directly with engineers and product leaders while owning science end-to-end, from concept through launch. This team is not training foundation models; it is advancing how they are applied through agentic architectures and evaluation.

Key Responsibilities:

- Design agentic systems for reasoning, tool use, planning, and orchestration
- Apply reinforcement learning to improve routing and task resolution




- Build evaluation frameworks, benchmarks, and regression detection pipelines
- Prototype AI-powered features from concept through production launch
- Design experiments that shape architecture and product roadmaps

Requirements:

- Three-plus years building machine learning models for business applications
- PhD, or master's degree and four-plus years of relevant experience
- Patents or publications in top-tier peer-reviewed venues
- Programming experience in Java, C++, Python, or related languages
- Experience with machine learning, reinforcement learning, or related applications

Bring applied science, reinforcement learning, and evaluation expertise to build agentic Alexa experiences serving millions of customers daily.

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📌 Applied Scientist Agentic AI Systems (British Columbia)
🏢 Amazon
📍 British Columbia