Software Dev Engineer Machine Learning

Amazon Amazon · Big Tech · M, Spain +1 · Software Development

Software Development Engineer Machine Learning role focused on improving video and audio streaming experience for smart home devices. The role involves optimizing ML/AI frameworks for real-time inference, optimizing training pipelines, analyzing model performance, and leveraging GenAI tools for development productivity. It requires experience with video/image processing, computer vision, machine learning, and cloud computing, with a focus on scalable services and distributed systems.

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

  • video and image processing and compression algorithms and standards
  • computer vision
  • machine learning
  • cloud computing
  • Python
  • Java
  • C++
  • Data structures implementation
  • Basic algorithm development
  • Object-oriented design principles

Nice to have

  • technical internship(s)
  • demonstrated project experience
  • video embedded
  • on-device ML model optimization for embedded/resource-constrained hardware
  • 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
  • problem-solving and analytical skills
  • written and verbal communication skills
  • learn and adapt to new technologies quickly
  • software development lifecycle (SDLC)

What the JD emphasized

  • real-time inference on device and cloud
  • optimizing training pipelines
  • analyzing model performance metrics
  • design reviews for new ML features
  • GenAI and AI-powered tools to enhance development productivity

Other signals

  • ML/AI frameworks for real-time inference on device and cloud
  • optimizing training pipelines
  • analyzing model performance metrics
  • design reviews for new ML features
  • GenAI and AI-powered tools to enhance development productivity