Applied Scientist (genai/llm), Sandstone

Amazon Amazon · Big Tech · Seattle, WA · Machine Learning Science

Applied Scientist role focused on building foundational behavioral models for Amazon Stores using Generative AI, LLMs, and large model training techniques. The role involves researching and implementing new algorithms, optimizing model performance for inference, and collaborating on data preprocessing and training infrastructure. It requires a PhD or Master's with 4+ years of experience in CS/ML, 2+ years of building models for business applications, and experience with programming languages and ML tools. Familiarity with NLP and computer vision is preferred.

What you'd actually do

  1. Research and implement new algorithms and architectures for generative AI applications.
  2. Optimize model performance and scalability for inference and deployment.
  3. Collaborate with other talented applied scientists and engineers to gather and preprocess large datasets and develop an improved training infrastructure that accelerates innovation.
  4. Experiment with SOTA methods to improve generative AI model quality.
  5. Provide technical expertise and guidance to support the integration of generative AI solutions into various products and services.

Skills

Required

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • 2+ years of building models for business application experience
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals

Nice to have

  • Strong understanding of machine learning, deep learning, and generative AI principles and algorithms.
  • Proficiency with modeling and large-scale data processing tools such as Pytorch, scikit-learn, Spark MLLib, PySpark, MxNet, Tensorflow, numpy, scipy etc.
  • Ability to work with large datasets and knowledge of data preprocessing techniques such as Hadoop, Spark etc..
  • Familiarity with natural language processing (NLP) and computer vision for generative AI applications.
  • Strong problem-solving and critical thinking skills and excellent communication and teamwork abilities to collaborate with cross-functional teams.
  • Ability to stay updated with the latest advancements in generative AI and adapt to new techniques and methodologies.

What the JD emphasized

  • foundational behavioral models
  • Generative AI
  • LLMs
  • Large Model training
  • Amazon e-commerce domain knowledge
  • rigorous testing
  • successful deployment
  • building models for business application experience
  • patents or publications at top-tier peer-reviewed conferences or journals

Other signals

  • Generative AI
  • LLMs
  • Large Model training
  • behavioral models
  • foundational models