Applied Scientist

Amazon Amazon · Big Tech · Newark, NJ · Applied Science

Applied Scientist role focused on developing and deploying production-ready AI/ML models for consumer-facing features like content understanding, recommendations, and GenAI applications. The role involves inventing new approaches, adapting existing ones, and building scalable, efficient solutions. It requires collaboration with scientists and engineers, with a focus on both scientific and engineering best practices, and potentially contributing to research papers. The role touches on inference infrastructure and model serving, with a primary focus on building agentic or product-level AI features.

What you'd actually do

  1. Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined
  2. Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
  3. Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
  4. Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex
  5. Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment

Skills

Required

  • Knowledge of data structures, algorithm design, statistics, and system design
  • MSc + 5 years of relevant experience, or PhD +1 year in Machine Learning, Computer Science, Computer Engineering, Data Science, Applied Math, or a related quantitative field
  • 3+ years of experience in Deep Learning, Natural Language Processing/Understanding, GenAI and/or Reinforcement Learning
  • Proficiency in Python, SQL, and other scripting languages
  • Experience employing and innovating with LLMs/GenAI to solve complex problems

Nice to have

  • 2+ years of practical machine learning experience
  • Experience in agile software development methodology
  • Experience with programming languages such as Python, Java, C++
  • Have publications at top-tier peer-reviewed conferences or journals
  • Experience with building Recommendation Systems
  • Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms

What the JD emphasized

  • production-ready models
  • inventing or adapting scientific approaches, models, and algorithms
  • develop reusable science components and services
  • design, develop, and deploy modeling techniques and solutions
  • employing and innovating with LLMs/GenAI to solve complex problems
  • Machine Learning Pipeline orchestration

Other signals

  • deploying production-ready models
  • inventing or adapting scientific approaches, models, and algorithms
  • develop reusable science components and services
  • design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features