Cryptography Intern - Apple Services Engineering
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, smart people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple products. We are offering amazing internship opportunities to work directly with our cryptography team in Paris, France. Collaborate with some of the best in the business and see how we create the world's most innovative products and experiences.
Our aim is to protect services on devices as close as possible to where they are consumed. With the advent of machine learning it means we need to integrate cryptographic software to encrypt, decrypt and authenticate data onto other computing units than the main CPU of the Apple Silicon SoCs. This includes the Apple Neural Engine or the GPUs of the SoCs. Protecting machine learning models on device could be done through cryptographic computations using the computing units dedicated to ML.
You will join an extraordinary team, including world-class software engineers and cryptographers. We will partner you with a dedicated mentor who is an experienced member of our team. You will focus on implementing symmetric encryption algorithms to be run on the Apple Neural Engine and potentially the GPU on the Apple Silicon SoC. You will have to search for ideas to make the implementation as efficient as possible to take advantage of all the hardware optimizations available for inferences.
- MSc in computer science or mathematics with a major in cryptography or equivalent
- Student studying computer science or mathematics with a major in cryptography
- Strong knowledge of cryptographic algorithms
- Strong programming, debugging and problem solving skills
- Proficiency in more than one programming language, such as Python, C, C++
- Interest in machine learning and familiarity with ML languages