UK Internship Program
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
CUDA @ 3 GPU @ 3Details
Perplexity is excited to announce the Internship Program for exceptional Master’s and PhD students (or recent graduates) in AI or Computer Science in the UK. This is an intensive program in which you will work directly with our AI Inference team to support the inference engines serving the models behind Perplexity. This program offers a unique opportunity to gain valuable experience in a rapidly growing AI startup. Outstanding performers might be offered a full time position at the end of the program.
Responsibilities
- Work with the inference team to improve serving latency and throughput
- Bring up support for new models and accelerate inference for existing ones
- Optimize inference across the entire stack, from GPU kernels to serving endpoints
Requirements
- Pursuing a Master's or PhD (or recently graduated) in Computer Science with a focus on Artificial Intelligence or Performance
- Experience with ML frameworks (Torch, JAX)
- Experience with GPU programming (CUDA, Triton)
- Experience with High-Performance Computing (OpenMPI)
Schedule
- Internship program: 7 July - 3 October 2025 (13 weeks), full-time or part-time, in-person in London office (hybrid schedule: 3 days from the office, 2 days WFH)
Compensation
- £35-40/h gross
- Laptop is provided
Additional Information
- Visa sponsorship is not available
- University approval required for student visa holders
- 2-3 internship spots available
- Housing and health insurance are not provided for interns; full-time employees receive health insurance and benefits
- Unlimited full-time offers available for outstanding performers
The company has experienced significant growth, increasing daily query handling from 2.5 million to around 20 million in less than a year, and has a strong investor base including notable technology investors.
Final offer amounts are based on multiple factors including experience and expertise and may vary from the listed amounts.