Applied Scientist Ii, Alexa International Team

Amazon Amazon · Big Tech · Bellevue, WA · Applied Science

Applied Scientist II on the Alexa International Team at Amazon, focusing on developing novel algorithms and modeling techniques for Large Language Models (LLMs) and multimodal systems. The role involves fine-tuning/post-training LLMs, building evaluation metrics, and contributing to end-to-end delivery of solutions impacting international customers.

What you'd actually do

  1. Analyze, understand, and model customer behavior and the customer experience based on large-scale data.
  2. Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants.
  3. Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF.
  4. Set up experimentation frameworks for agile model analysis and A/B testing.
  5. Collaborate with partner teams on LLM evaluation frameworks and post-training methodologies.

Skills

Required

  • deep learning
  • generative models
  • LLM architectures
  • LLM evaluation
  • Python
  • algorithms
  • data structures
  • parsing
  • numerical optimization
  • data mining
  • parallel and distributed computing
  • high-performance computing

Nice to have

  • professional software development
  • speech recognition
  • machine translation
  • natural language processing
  • machine learning models for business application

What the JD emphasized

  • novel algorithms
  • modeling techniques
  • LLMs
  • multimodal systems
  • international customers
  • LLM evaluation & tooling
  • pushing boundaries
  • fast-paced environments
  • complex challenges
  • swiftly delivering impactful solutions
  • iterating based on user feedback
  • collaborate effectively
  • novel online & offline evaluation metrics and methodologies
  • fine-tune/post-train LLMs
  • experimentation frameworks
  • agile model analysis
  • A/B testing
  • LLM evaluation frameworks
  • post-training methodologies
  • end-to-end delivery of solutions
  • reusable science components
  • publications
  • patents or publications at top-tier peer-reviewed conferences or journals

Other signals

  • LLMs
  • multimodal systems
  • deep learning
  • generative models
  • international products