Principal Data Scientist, Wwps Proserve

Amazon Amazon · Big Tech · Arlington, VA · Project/Program/Product Management--Technical

Principal Data Scientist role at Amazon ProServe, focusing on architecting and implementing enterprise-scale AI/ML and generative AI solutions for customers. Requires technical leadership, strategic advisory, and developing reusable frameworks. Involves customer-facing engagements and mentoring junior data scientists. Requires Top Secret clearance.

What you'd actually do

  1. Architecting and implementing complex, enterprise-scale AI/ML solutions that solve critical customer business challenges
  2. Providing technical leadership across multiple customer engagements, establishing best practices and driving innovation
  3. Collaborating with Delivery Consultants, Engagement Managers, Account Executives, and Cloud Architects to design and deploy AI/ML solutions
  4. Developing reusable solution frameworks, reference architectures, and technical assets that accelerate customer adoption of AWS AI/ML services
  5. Representing AWS as a subject matter expert in customer-facing engagements, including executive briefings and technical workshops

Skills

Required

  • Python
  • TensorFlow
  • PyTorch
  • Hugging Face
  • Machine Learning fundamentals
  • Large Language Model fundamentals
  • architecture
  • training/inference lifecycles
  • optimization of model execution
  • vLLM
  • SGLang
  • TensorRT
  • production environments

Nice to have

  • AWS Professional level certification
  • PhD in computer science, machine learning, engineering, or related fields
  • MS degree
  • IT and/or Management Consulting experience
  • patents or publications at top-tier peer-reviewed conferences or journals

What the JD emphasized

  • US Citizen and currently possess and maintain an active Top Secret security clearance
  • 11+ years of building machine learning models or developing algorithms for business application experience
  • Deep expertise in Python and relevant ML frameworks (TensorFlow, PyTorch, Hugging Face, etc.)
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience with vLLM, SGLang, TensorRT or similar platforms in production environments

Other signals

  • Architecting and implementing complex, enterprise-scale AI/ML solutions
  • technical leader and strategic advisor to AWS enterprise customers
  • translate business challenges into technical solutions
  • drive innovation through thought leadership
  • develop reusable solution frameworks