Job opportunity
Applied Scientist Agentic AI Systems
Amazon
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.
#J-18808-Ljbffr
Apply on source site 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.
#J-18808-Ljbffr