Applied Scientist, Aice - AI Center of Excellence

Amazon Amazon · Big Tech · CA, BC +1 · Machine Learning Science

Research Scientist role focused on building and hardening AI primitives for enterprise-wide consumption at Amazon, translating research into production-ready solutions and driving scientific direction.

What you'd actually do

  1. Research, design, and develop AI/ML primitives - defining problem spaces, formulating approaches, running experiments, and validating outcomes with scientific rigor
  2. Translate research findings into production-ready primitives, working closely with machine learning engineers to harden and scale solutions
  3. Drive the scientific direction of AICE primitives, identifying opportunities where novel approaches can unlock step-function improvements
  4. Design and execute experiments to validate primitive performance, robustness, and generalizability before broad consumption by partner teams
  5. Collaborate with product-owning teams to understand their problem spaces and ensure AICE primitives deliver measurable value when integrated

Skills

Required

  • PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
  • Experience with programming languages such as Python, Java, C++
  • Ability to work across the research-to-production spectrum - from formulating hypotheses to validating primitives in production environments
  • Familiarity with traditional software development practices with the ability to also leverage AI-assisted development tools effectively
  • Experience designing and running experiments, A/B tests, or rigorous offline evaluations
  • Track record of translating research into applied solutions that operate at scale
  • Strong foundation in statistical methods, experimental design, and model evaluation

Nice to have

  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience building reusable ML/AI components, frameworks, or primitives consumed by other teams
  • Experience in information retrieval, knowledge representation, or agentic AI systems
  • Demonstrated ability to collaborate with engineering teams to harden research prototypes for production

What the JD emphasized

  • PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
  • Track record of translating research into applied solutions that operate at scale
  • Experience building reusable ML/AI components, frameworks, or primitives consumed by other teams

Other signals

  • builds AI primitives
  • translate research into hardened, reusable primitives
  • drive the scientific direction
  • publish findings
  • building the AI primitives that power Amazon's intelligent systems
  • building reusable ML/AI components, frameworks, or primitives consumed by other teams