What You’ll Be Doing
Design and evolve scalable architectures for multi-node LLM inference across GPU clusters.
Develop infrastructure to optimize latency, throughput, and cost-efficiency of serving large models in production.
Collaborate with model, systems, compiler, and networking teams to ensure complete, high-performance solutions.
Prototype novel approaches to KV cache handling, tensor/pipeline parallel execution, and dynamic batching.
Evaluate and integrate new software and hardware technologies relevant to Core Spectrum-X technologies, such as load balancing, telemetry, congestion control, vertical application integration.
Work closely with internal teams and external partners to translate high-level architecture into reliable, high-performance systems.
Author design documents, internal specs, and technical blog posts and contribute to open-source efforts when appropriate.
What We Need to See
Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or equivalent experience.
8+ years of experience building large-scale distributed systems or performance-critical software.
Deep understanding of deep learning systems, GPU acceleration, and AI model execution flows and/or high performance networking.
Proven software engineering skills in C++ and/or Python, preferably demonstrate strong familiarity with CUDA or similar platforms.
Strong system-level thinking across memory, networking, scheduling, and compute orchestration.
Excellent communication skills and ability to collaborate across diverse technical domains.
Ways to Stand Out from the Crowd
Experience working on LLM - training or inference pipelines, transformer model optimization, or model-parallel deployments.
Proven success in profiling and optimizing performance bottlenecks across the LLM training or inference stack.
AI Accelerators and distributed communication patterns, congestion control and/or load balancing.
Shown optimization process for complex systems, deployed at scale to make impact.
Proven experience successfully driving complex organizational processes from planning through implementation.
NVIDIA is widely considered one of the most desirable places to work in tech – we are passionate about what we do and are committed to fostering a culture of perfection, innovation, and collaboration. If you’re excited to help define how the world runs AI at scale, this role is for you. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. While planning your future, explore the benefits available to you and your family at www.nvidiabenefits.com/