Software Dev Engineer Internship - Machine Learning

Pioneer the future of AI and Machine Learning at Amazon! Join elite teams developing cutting-edge ML solutions that power Amazon Q's intelligent chat, revolutionize European operations through computer vision, transform retail search, and enhance Amazon Music recommendations for millions of customers worldwide.
Collaborate with world-class ML engineers and scientists to build and deploy state-of-the-art models in natural language processing, computer vision, and recommendation systems. Shape the next generation of AI-powered products while learning from industry experts in a fast-paced, innovation-driven environment
Applicants will be reviewed on a rolling basis and are matched to teams aligned with their experience plus location and availability preferences prior to interviews. Applicants will remain under consideration until we have assessed all potential team matches or finished recruiting.
This role may available across multiple locations in the EMEA region (France, Germany, Italy, Luxembourg Poland, Romania, Spain, and the UK) and you can indicate the locations you’re open to when applying.
Internship start dates generally take place between April to October (inclusive) of any given year with some exceptions.
Internships durations are typically either 3 or 6 months with some exceptions and you can also indicate your availability during the application process
Please note these are not remote positions.

Key job responsibilities
• Develop and optimize ML models for production deployment at massive scale
• Design and implement efficient ML pipelines and data processing systems
• Create and enhance evaluation frameworks for model performance
• Build and maintain MLOps infrastructure and tools
• Contribute to the development of innovative prompting and retrieval strategies
• Implement solutions for real-time inference and model serving
• Work on large-scale distributed training systems
• Collaborate with cross-functional teams to integrate ML solutions into products

A day in the life
As an intern, you'll be paired with both a manager and a mentor who will guide your development. Your day might include:
• Attending team stand-ups and technical design reviews
• Implementing and testing new ML models and algorithms
• Analyzing model performance metrics and conducting A/B tests
• Collaborating with scientists to improve model architectures
• Working with senior engineers on ML infrastructure design
• Participating in code reviews and documentation
• Learning about cutting-edge ML technologies and best practices
• Contributing to real AI products used by millions of customers

BASIC QUALIFICATIONS

- Must be 18 years of age or older
- Education Requirements (must meet one):
- oCurrently enrolled in Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Information Systems, or related STEM fields [degrees can be updated based on regional variations]
- o Completed Bachelor's or Graduate degree in specified fields
- Expected graduation between October 2026 - September 2029
- Demonstrated experience with at least one general-purpose programming language such as Java, Python, C++, C#, Go, Rust, or TypeScript
- Demonstrated experience one or more of the following:
- o Data structures implementation
- o Basic algorithm development
- o Object-oriented design principles

PREFERRED QUALIFICATIONS

- 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
- Previous technical internship(s) or demonstrated project experience
- Experience with one or more of the following:
- o AI tools for development productivity
- o Cloud platforms (preferably AWS)
- o Database systems (SQL and NoSQL)
- o Contributing to open-source projects
- o Version control systems
- o 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)