Amazon.com Services LLC
Technology
AppliedScientist,ConversationalAssistantModelingandLearning
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Applied Scientist, Conversational Assistant Modeling and Learning at Amazon.com Services LLC. Skills: Machine Learning, Data Engineering, Statistical Modeling. Design and implement machine learning models. Develop and maintain data pipelines”
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Master's degree, 3+ years of experience
Nice to Have
PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification
What You'll Do.
Design and implement machine learning models
Develop and maintain data pipelines
Conduct data analysis
Build and deploy ML systems
Collaborate with engineering teams
Stay current with ML research
How You'll Work.
Team & Collaboration
Cross-functional teams; Engineering teams
Full Job Description
Alexa AI is looking for an Applied Scientist to build Alexa+, Amazon's LLM-powered conversational assistant. You will work on key initiatives spanning large language model fine-tuning, alignment, agentic reasoning, and evaluation — directly shaping the experience for hundreds of millions of customers worldwide. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with other scientists and engineers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Key job responsibilities * Improve the efficiency of LLM, VLM, and agent training and evaluation pipelines, including distributed training, inference serving, data loading, checkpointing, memory usage, and GPU utilization. * Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment * Architect agentic systems — multi-step reasoning, tool use, planning, and orchestration * Develop evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality * Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams * Publish results at top-tier venues and represent Amazon in the broader research community About the team Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning, agentic architectures
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