AI Inference Engineer
at Perplexity AI
Posted 12 hours ago
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Join our team as an AI Inference Engineer working on real-time, large-scale deployment of ML models. You'll work with Python, Rust, C++, PyTorch, Triton, CUDA, and Kubernetes to build and optimize inference APIs used by internal and external customers. Responsibilities include benchmarking bottlenecks, improving reliability and observability, and researching LLM inference optimizations for performance and latency.
We are looking for an AI Inference engineer to join our growing team. Our current stack is Python, Rust, C++, PyTorch, Triton, CUDA, Kubernetes. You will have the opportunity to work on large-scale deployment of machine learning models for real-time inference.
Responsibilities
Develop APIs for AI inference that will be used by both internal and external customers
Benchmark and address bottlenecks throughout our inference stack
Improve the reliability and observability of our systems and respond to system outages
Explore novel research and implement LLM inference optimizations
Qualifications
Experience with ML systems and deep learning frameworks (e.g. PyTorch, TensorFlow, ONNX)
Familiarity with common LLM architectures and inference optimization techniques (e.g. continuous batching, quantization, etc.)
Understanding of GPU architectures or experience with GPU kernel programming using CUDA
