We are looking for a senior software engineer to contribute to building accelerated microservices and libraries for our harnesses and agents. In this role, you will be part of an engineering team designing and developing microservices and libraries and optimizing these for relevant metrics.
What you will be doing:
- Contribute to design and development of accelerated microservices and libraries
- Collaborate with peer engineering and Product Management teams to understand requirements and translate these into deliverables across milestones.
- Design, develop, and maintain real-time vision-language model inference microservices, from video ingestion and preprocessing through model serving and downstream integration.
- Develop automated functional, accuracy, and performance regression tests, and own component readiness through integration, release, and post-release debugging.
- Profile and optimize end-to-end latency, throughput, GPU memory usage, and concurrent user capacity across platforms.
What we need to see:
- Masters or Bachelors degree in Computer Science, or related engineering field
- 8+ years of overall experience in software development , a strong technical foundation in software design principles and strong programming skills in C/C++ and Python.
- Hands-on experience building microservices using containers, REST APIs, and asynchronous messaging.
- Hands-on experience integrating and serving computer vision and vision-language models in production.
- Understanding of real-time video processing and the tradeoffs among latency, throughput, and resource utilization and strong debugging skills.
- Experience evaluating model quality and diagnosing accuracy or performance regressions across model, preprocessing, and inference-runtime changes.
Ways to stand out from the crowd:
- Experience delivering end-to-end video AI applications, including video ingestion, inference, tracking, analytics, and downstream integrations, using technologies such as RTSP and FFmpeg.
- Background with NVIDIA DeepStream, TensorRT, Triton Inference Server, CUDA, or comparable technologies.
- Experience optimizing and profiling GPU inference pipelines, including batching, memory management, and concurrent model execution.
- Experience with stateful streaming inference, KV-cache management, batching, quantization, and their impact on serving performance.
- Experience profiling GPU applications with tools such as NVIDIA Nsight Systems and deploying inference services across x86 and ARM platforms.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and passionate people in the world working for us. Are you a creative problem solver with a passion for solving real-world problems with AI? If so, we want to hear from you.
Skills Required
- Bachelor’s or master’s degree in Computer Science or a related engineering field
- 8+ years of software development experience
- Strong software design and programming skills in C/C++ and Python
- Experience building microservices using containers, REST APIs, and asynchronous messaging
- Experience integrating and serving computer vision and vision-language models in production
- Understanding of real-time video processing and latency, throughput, and resource utilization tradeoffs
- Strong debugging skills
- Experience evaluating model quality and diagnosing accuracy or performance regressions
- Experience delivering end-to-end video AI applications using RTSP and FFmpeg
- Experience with NVIDIA DeepStream, TensorRT, Triton Inference Server, CUDA, or comparable technologies
- Experience optimizing and profiling GPU inference pipelines
- Experience with stateful streaming inference, KV-cache management, batching, and quantization
- Experience using NVIDIA Nsight Systems and deploying inference services across x86 and ARM platforms
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Feedback suggests equity grants, stock options/RSUs, and a discounted ESPP materially boost total compensation and can deliver significant wealth-building when the stock performs well.
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Healthcare Strength — Feedback suggests medical, dental, and vision plans with in-network preventive care at 100%, telehealth, and concierge-style support are comprehensive and valued.
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Parental & Family Support — Feedback suggests up to 22 weeks fully paid parental leave, fertility coverage, and adoption/surrogacy reimbursement provide strong family-focused benefits.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
