Sr. Applied Scientist, Special Projects

Amazon Amazon · Big Tech · NY +1 · Applied Science

This role is for a Sr. Applied Scientist on an Amazon Special Projects team focused on creating new products and services. The role involves leading research projects from ideation to production, driving ML/AI strategy, collaborating cross-functionally, publishing findings, and establishing best practices for ML experimentation and deployment. Requires a PhD or Master's with significant applied research experience, strong programming skills, and experience with ML/LLM fundamentals and deploying ML systems at scale. Experience with autonomous AI frameworks and translating research into production systems is preferred.

What you'd actually do

  1. Lead and execute complex, ambiguous research projects from ideation to production deployment
  2. Drive technical strategy and roadmap decisions for ML/AI initiatives
  3. Collaborate cross-functionally with product, engineering, and business teams to translate research into scalable products
  4. Publish research findings at top-tier conferences and contribute to the broader scientific community
  5. Establish best practices for ML experimentation, evaluation, and deployment

Skills

Required

  • PhD or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience delivering results for large, cross-functional initiatives/projects
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
  • Experience with training and deploying machine learning systems to solve large-scale optimizations

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development
  • Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
  • Experience providing technical leadership on high-impact cross-fucntional technical project
  • Experience with autonomous AI frameworks (e.g. Dreamer, PlaNet, JEPA, NVIDIA Cosmos)
  • Knowledge of decentralized optimization methods (e.g. swarm intelligence)
  • Familiarity with advanced optimization and control methods (multi-objective optimization, constrained optimization, discrete optimization, model-based optimization, stochastic optimization, distributed control)
  • Experience developing and maintaining digital twins
  • Experience with multiscale geospatial modeling and forecasting
  • Track record of translating research into production systems at scale

What the JD emphasized

  • production deployment
  • scalable products
  • Machine Learning and Large Language Model fundamentals
  • training and deploying machine learning systems to solve large-scale optimizations
  • translating research into production systems at scale

Other signals

  • Lead and execute complex, ambiguous research projects from ideation to production deployment
  • Drive technical strategy and roadmap decisions for ML/AI initiatives
  • Collaborate cross-functionally with product, engineering, and business teams to translate research into scalable products
  • Establish best practices for ML experimentation, evaluation, and deployment