Senior Applied Scientist, Pxt

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

Senior Applied Scientist role focused on developing and deploying GenAI/LLM solutions within Amazon's People eXperience Technology (PXT) team. The role involves end-to-end ML solution development, from research and experimentation to production deployment, with an emphasis on building scalable, reliable, and cost-efficient AI systems. Responsibilities include prompt engineering, fine-tuning, model evaluation, and technical leadership, aiming to improve Amazonians' well-being and work. The role also involves mentoring junior scientists and contributing to the team's science strategy.

What you'd actually do

  1. Design and implement novel GenAI/LLM solutions using foundation models (e.g., Claude, GPT) and AWS services including Amazon Bedrock, SageMaker, and other AWS AI/ML tools
  2. Conduct applied research to advance the state-of-the-art in LLM applications, including prompt engineering, few-shot learning, fine-tuning, and model evaluation
  3. Build scalable, production-ready AI systems that serve millions of requests with high reliability, low latency, and cost efficiency
  4. Partner with product managers, engineers, and business stakeholders to translate business requirements into technical solutions and drive measurable impact
  5. Mentor junior scientists, contribute to technical strategy, and establish best practices for GenAI development across the organization

Skills

Required

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Nice to have

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.

What the JD emphasized

  • translating innovative science into impactful products
  • end-to-end ML solutions from problem formulation to deployment
  • novel GenAI/LLM solutions
  • applied research to advance the state-of-the-art in LLM applications
  • scalable, production-ready AI systems
  • rigorous evaluation frameworks to measure model performance, bias, safety, and business impact

Other signals

  • develop end-to-end ML solutions from problem formulation to deployment
  • mentor junior scientists
  • design and implement novel GenAI/LLM solutions
  • build scalable, production-ready AI systems