Amazon Principal Applied Scientist Amazon Q 

United States, California 

897424313

You’ll work on building and optimizing multi-modal foundation models, training and fine-tuning state-of-the-art LLMs, and architecting systems that scale efficiently across domains. This role blends science leadership, hands-on innovation, and deep collaboration with engineering teams to bring research into production.Key job responsibilities
Lead the design and development of foundational models and intelligent agent architectures tailored to enterprise use cases.Drive experimentation to improve model accuracy, safety, latency, and cost efficiency.Contribute to and publish in top-tier conferences or file patents based on novel research contributions.

- PhD in Machine Learning, Computer Science, Electrical Engineering, or a related technical field OR a Master’s degree with 5+ years of relevant industry or research experience.- Industry experience developing machine learning models for real-world applications.- Experience with generative AI, including model training or building systems with pre-trained foundation models.- Proven record of peer-reviewed publications or granted patents in AI/ML.- Proficiency in Python or similar programming languages.- Experience in at least one of the following areas: natural language processing (NLP), large language models (LLMs), computer vision, or Agentic AI.

- Experience applying generative AI to enterprise or multi-modal tasks (e.g., code generation, document understanding, or task planning).- Strong understanding of agentic architectures, autonomous systems, or task orchestration.- Hands-on experience with scalable ML infrastructure, distributed training, or optimization of large models.- Deep knowledge of AI safety, hallucination mitigation, or retrieval-augmented generation (RAG).- Experience mentoring junior scientists and influencing cross-functional stakeholders.- Ability to think strategically and communicate complex technical topics to non-experts, including senior leadership.