Software Dev Engineer Intern Machine Learning, Amazon Robotics

Amazon Amazon · Big Tech · DE, Belgium +1 · Software Development

Software Development Engineer Intern Machine Learning, Amazon Robotics. The role involves simplifying ML training infrastructure, extending monitoring of ML trainings, and potentially developing perception models for warehouse robots. It requires experience with AI, Neural Networks, Tensorflow, and PyTorch, and focuses on building scalable ML solutions within a robotics context.

What you'd actually do

  1. Collaborate and communicate effectively with experienced cross-disciplinary Amazonians to design, build, and operate innovative products and services that delight our customers, while participating in technical discussions to drive solutions forward.
  2. Design and develop scalable solutions using cloud-native architectures and microservices in a large distributed computing environment.
  3. Participate in code reviews and contribute to technical documentation.
  4. Build and maintain resilient distributed systems that are scalable, fault-tolerant, and cost-effective.
  5. Leverage and contribute to the development of GenAI and AI-powered tools to enhance development productivity while staying current with emerging technologies.

Skills

Required

  • AI
  • Neural Network
  • Tensorflow
  • PyTorch
  • Data structures implementation
  • Basic algorithm development
  • Object-oriented design principles

Nice to have

  • AI tools for development productivity
  • Cloud platforms (preferably AWS)
  • Database systems (SQL and NoSQL)
  • Contributing to open-source projects
  • Version control systems
  • Debugging and troubleshooting complex systems
  • Strong problem-solving and analytical skills
  • Excellent written and verbal communication skills
  • Demonstrated ability to learn and adapt to new technologies quickly
  • Basic understanding of software development lifecycle (SDLC)

What the JD emphasized

  • Demonstrated experience with AI, Neural Network, Tensorflow, PyTorch

Other signals

  • ML training infrastructure
  • monitoring of ML trainings
  • perception models