
GPU Internships - Platform Architecture
- Cambridge
- Training
- Full-time
- Currently pursuing a BS, MS, or PhD in Computer Science, Electrical Engineering, Computer Engineering, Electrical and Computer Engineering, or a related field.
- At the end of the internship, you must return to school to continue your education or the internship must be the last requirement for you to graduate.
- Strong coding skills including object-oriented programming with C and C++
- Knowledge of scripting languages such as Perl, Python or Ruby
- Strong understanding of common data structures, algorithms, and design patterns
- A curiosity about GPU / CPU / SOC architecture and micro-architecture
- Strong interpersonal and analytical skills, with an ability to make data driven decisions
- Ability to work well within a team and be productive under tight schedules
- Knowledge of performance modelling, logic design and power
- Curiosity about machine learning and classification algorithm
- Experience optimising rendering/parallel compute algorithms, drivers and/or compilers for one or more GPU architectures
- Prior experience on hardware architectural modelling and hardware description languages
- Experience with one or more GPU APIs (Metal, DX12, Vulcan, CUDA, OpenGL, OpenCL)