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UK Internship Program

Salary

35 - 40 GBP

Min Experience

0 years

Location

London

JobType

internship

About the job

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About the role

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 Qualifications: 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)

About the company

At Perplexity, we've experienced tremendous growth and adoption since publicly launching the world's first fully functional conversational answer engine in 2022. We've grown from answering 2.5 million questions per day at the start of 2024 to around 20 million daily queries in December 2024. We also offer Perplexity Enterprise Pro, which counts leading companies like Nvidia, the Cleveland Cavaliers, Bridgewater, and Zoom as customers. To support our rapid expansion, we've raised significant funding from some of the most respected technology investors. Our investor base includes IVP, NEA, Jeff Bezos, NVIDIA, Databricks, Bessemer Venture Partners, Elad Gil, Nat Friedman, Daniel Gross, Naval Ravikant, Tobi Lutke, and many other visionary individuals. In 2024, our employee base grew nearly 300%, and we're just getting started.

Skills

machine learning
computer science
gpu programming
high-performance computing