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Member of Technical Staff (AI Inference Engineer)

Perplexity· AI Research & Systems
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LondonFull-timePosted 11mo ago

About the role

AI Inference Engineer responsible for building and running the inference engine behind Perplexity queries, deploying multiple model architectures at scale with low latency and cost, using Rust, Python, CUDA, and CuTe DSL.

Responsibilities

  • New models support. Support transformer-based retrieval, text-generation, and multimodal models in our inference infrastructure, from weight loading, request scheduling and KV-cache management to support in API Gateway.
  • GPU kernels migration to CuTe DSL. Port our in-house CUDA kernels to NVIDIA's CuTe DSL so they run on GB200 today and are portable to Vera Rubin racks tomorrow.
  • Rust-native serving runtime. Develop our internal Rust-based inference server to solve all Python pains and keep up with rapidly growing traffic.
  • Performance optimisation. Profile and fix bottlenecks from network ingress through continuous batching and GPU kernels interleaving.
  • Reliability and observability. Build dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.

Qualifications

  • 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.
  • Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).
  • Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).
  • Understanding of common LLM architectures and inference optimization techniques (e.g. quantization, speculative decoding, prefill-decode disaggregation).

Skills

Required:GPU programming and performance optimizationRustPythonCUDA/CuTe DSLLLM architectures and inference optimization
Nice to have:Distributed systems
Last updated Jul 15, 2026. Interested? Apply on the company site.

About Perplexity

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