Real-Time Inference Systems Architect (GPU & On-Device)

Genesis AI; San Carlos (CA); Presencial; USD 180 000 - 240 000; Tempo integral

Resumo da oferta

Genesis AI is seeking an expert to build and optimize real-time inference systems for on-device and cluster deployments. You will implement low-level CUDA/Triton kernels and integrate them with high-level AI frameworks, with a focus on both throughput and latency.

You will lead design and optimization of scalable ML infrastructure, ensuring reliability, determinism, and efficient resource usage across GPU clusters and edge devices.

Qualificações

• 8+ years of experience in distributed systems, ML infrastructure, or high-performance serving.
• Production-grade Python with strong systems languages background (C++, Rust, Go).
• Low-level performance mastery in CUDA, Triton, kernel optimization, quantization, and memory/compute scheduling.

Responsabilidades

• Build low-latency inference pipelines for on-device deployment in robotics.
• Design and optimize distributed inference systems on GPU clusters for high throughput.
• Implement low-level code (CUDA, Triton, custom kernels) and integrate into high-level frameworks.
• Optimize workloads for throughput and latency through batching, quantization, caching, and memory management.
• Develop monitoring and debugging tools for reliability and rapid diagnosis of regressions.

Conhecimentos

Distributed systems

Python

C++

Rust

Go

Inference scaling

Ferramentas

CUDA

Triton

Kernel optimization

Quantization

Memory management

Compute scheduling

Descrição da oferta de emprego

Genesis AI is seeking an expert to build and optimize real-time inference systems for on-device and cluster deployments. You will implement low-level CUDA/Triton kernels and integrate them with high-level AI frameworks, with a focus on both throughput and latency.

You will lead design and optimization of scalable ML infrastructure, ensuring reliability, determinism, and efficient resource usage across GPU clusters and edge devices.