Amazon Software Dev Engineer ML 

United States, Washington, Seattle 

582373089

Key job responsibilities
• Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative products and services to market.
• Design and build innovative technologies in a large distributed computing environment and help lead fundamental changes in the industry.
• Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed.
• Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use.
• Design and code the right solutions starting with broadly defined problems.
• Work in an agile environment to deliver high-quality software.A day in the life

• Currently enrolled in or completed a Bachelor’s or Master’s Degree in Computer Science
• To qualify, applicants should have earned a Bachelor’s degree or higher between July 2023 to October 2024. Possible start dates for this role are between August 2024 to November 2024.
• Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design

• Previous technical internship(s), if applicable.
• Experience with distributed, multi-tiered systems, algorithms, and relational databases.
• Experience in optimization mathematics such as linear programming and nonlinear optimization.
• Ability to effectively articulate technical challenges and solutions.
• Adept at handling ambiguous or undefined problems as well as ability to think abstractly.
• Experience with Natural Language Processing, Computer Vision, or Deep Learning
• Experience with Natural Language Processing: Java or Python, and ML, AI, Labeling, Annotation, Data Pipeline, Big Data, AWS, or Cloud Services
• Experience with Computer Vision: Kernel, Hardware Accelerator, TVM, or Code-gen
• Experience with Deep Learning: C++ or Python, and AI, Neural Network, Tensorflow, PyTorch, MxNET, Llvm, Compiler, CPU, CUDA, Nvidia, TensorRT, TPU, Cluster Management, High Performance Computing, or Optimization