Deep Learning Architect, Aws Gen AI Innovation Center

Amazon Amazon · Big Tech · SP, Brazil +1 · Applied Science

This role involves designing, implementing, and fine-tuning state-of-the-art Generative AI solutions for AWS customers, focusing on real-world problem-solving and production deployment. The architect will collaborate with customers and internal teams to understand business needs, develop proof-of-concepts, and guide adoption patterns.

What you'd actually do

  1. Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
  2. Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
  3. Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
  4. Provide customer and market feedback to product and engineering teams to help define product direction

Skills

Required

  • Business English skills, both verbal and written
  • Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
  • 3+ years of experience in designing, building, and/or operating cloud solutions in a production environment
  • 2+ year experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
  • 2+ years of hands on experience with Python to build, train, and evaluate models
  • 2+ years of technical client engagement experience

Nice to have

  • Master's degree in computer science, computer engineering, or related field, or PhD
  • Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
  • Experience architecting/operating solutions built on AWS
  • Strong working knowledge of deep learning, machine learning, generative AI, and statistics
  • Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker

What the JD emphasized

  • designing, building, and/or operating cloud solutions in a production environment
  • hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
  • build, train, and evaluate models
  • technical client engagement experience
  • architecting/operating solutions built on AWS
  • building generative AI applications on AWS

Other signals

  • customer-facing
  • solution design
  • implementation
  • production deployment