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About the Role

Advance open-source LLM serving by contributing to inference engines like vLLM and SGLang, ensuring they run optimally on NVIDIA GPUs and systems. Improve the underlying stack for high-throughput, low-latency inference at scale. This is a hands-on role focused on performance bottlenecks, runtime improvements, and shipping community-beneficial changes.

Responsibilities

• Contribute features, fixes, and optimizations upstream to vLLM/SGLang, including authoring PRs, participating in reviews, writing benchmarks/tests, and driving designs.
• Implement and optimize inference-runtime capabilities such as batching, scheduling, streaming, request lifecycle management, and KV-cache efficiency.
• Profile and improve performance-critical code paths across various layers, from Python to C++/CUDA, using data to guide optimization.
• Enhance multi-GPU inference performance and reliability, focusing on parallelism, communication, and resource utilization.
• Build and maintain performance and correctness regression tests to ensure stable behavior across different configurations.
• Collaborate with model, platform, and SRE teams to translate production requirements into upstreamable solutions.

Requirements

• 5+ years of experience building production software with strong systems engineering fundamentals.
• Proven track record of delivering performance or reliability improvements.
• Experience with LLM inference/serving stacks (e.g., vLLM, SGLang) and understanding performance tradeoffs.
• Strong programming skills in Python and C++/CUDA, with the ability to debug and optimize performance-critical code.
• Experience with profiling and performance investigation techniques (microbenchmarks, flame graphs, GPU profiling).
• Familiarity with distributed systems concepts and concurrency.
• Strong communication skills and experience working with open-source communities.
• BS/MS in Computer Science, Computer Engineering, or related field, or equivalent experience.

Skills

• Python
• C++
• CUDA
• LLM inference/serving stacks
• vLLM
• SGLang
• Profiling
• Performance investigation
• Distributed systems
• Concurrency
• Open-source collaboration

Location

• Remote

Work Type

• Full-time

Experience Level

• Senior
• 5+ years

Education Level

• BS/MS in Computer Science, Computer Engineering, or related field, or equivalent experience.

Salary/Compensations

• 152,000 USD - 241,500 USD for Level 3
• 184,000 USD - 287,500 USD for Level 4

Benefits

• Equity
• Benefits

About the Company

• NVIDIA pioneered accelerated computing and its AI infrastructure powers global intelligence, transforming every industry.
• NVIDIA is considered one of the technology world's most desirable employers, with forward-thinking and creative people.
• NVIDIA uses AI tools in its recruiting processes.

Equal Opportunity

• NVIDIA is committed to fostering an inclusive work environment and is proud to be an equal opportunity employer.
• We do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.