Applied Scientist Ii, Alexa International

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Applied Science

Applied Scientist II with Alexa International focusing on LLMs and multimodal systems for international applications. Responsibilities include developing novel algorithms, building evaluation metrics, fine-tuning/post-training LLMs, conducting research, and leading end-to-end delivery of complex solutions from research to production.

What you'd actually do

  1. Develop novel algorithms and modeling techniques to advance the state of the art with LLMs, particularly delivering industry-leading scientific research and applied AI for multi-lingual applications
  2. Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants
  3. Fine-tune/post-train LLMs using advanced and innovative techniques like SFT, DPO, Reinforcement Learning (RLHF and RLAIF) for supporting model performance specific to a customer’s location and language
  4. Drive cross-team scientific strategy and influence partner teams on LLM evaluation frameworks, post-training methodologies, and best practices for international speech and language systems
  5. Lead end-to-end delivery of scientifically complex solutions from research to production, including reusable science components and services that resolve architecture deficiencies across teams

Skills

Required

  • Deep learning
  • Generative models
  • LLMs
  • Multimodal systems
  • Machine learning
  • Speech processing
  • Natural language processing
  • LLM evaluation
  • SFT
  • DPO
  • Reinforcement Learning (RLHF and RLAIF)
  • Java
  • C++
  • Python
  • Algorithms and data structures
  • Parsing
  • Numerical optimization
  • Data mining
  • Parallel and distributed computing
  • High-performance computing
  • Patents or publications at top-tier peer-reviewed conferences or journals

Nice to have

  • Unix/Linux
  • Professional software development

What the JD emphasized

  • industry-leading scientific research
  • multi-lingual applications
  • LLM evaluation & tooling
  • pushing boundaries
  • novel algorithms
  • modeling techniques
  • state of the art with LLMs
  • novel online & offline evaluation metrics and methodologies
  • advanced and innovative techniques
  • industry-first research
  • scientific thought leader
  • publications

Other signals

  • LLMs
  • multimodal systems
  • deep learning
  • generative models
  • multi-lingual applications
  • text, speech, and vision domains