Senior Software Engineer - Distributed Inference Job at NVIDIA, Austin, TX

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  • NVIDIA
  • Austin, TX

Job Description

Senior Software Engineer - Distributed Inference NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are now looking for a Senior System Software Engineer to work on user facing tools for Dynamo Inference Server. NVIDIA is hiring software engineers for its GPU-accelerated deep learning software team, and we are a remote friendly work environment. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in problems from LLM, image classification to speech recognition to natural language processing. We are a fast-paced team building tools and software to make the design and deployment of new deep learning models easier and accessible to more data scientists. What You’ll Be Doing Build and maintain distributed model management systems, including Rust-based runtime components, for large-scale AI inference workloads. Implement inference scheduling and deployment solutions on Kubernetes and Slurm, while driving advances in scaling, orchestration, and resource management. Collaborate with infrastructure engineers and researchers to develop scalable APIs, services, and end-to-end inference workflows. Create monitoring, benchmarking, automation, and documentation processes to ensure low-latency, robust, and production-ready inference systems on GPU clusters. What We Need To See Bachelor’s, Master’s, or PhD in Computer Science, ECE, or related field (or equivalent experience). 6+ years of professional systems software development experience. Strong programming expertise in Rust (with C++, Python as a plus). Deep knowledge of distributed systems, runtime orchestration, and cluster-scale services. Hands-on experience with Kubernetes, container-based microservices, and integration with Slurm. Proven ability to excel in fast-paced R&D environments and collaborate across functions. Ways To Stand Out From The Crowd Experience with inference-serving frameworks (e.g., Dynamo Inference Server, TensorRT, ONNX Runtime) and deploying/managing LLM inference pipelines at scale. Contributions to large-scale, low-latency distributed systems (open-source preferred) with proven expertise in high-availability infrastructure. Strong background in GPU inference performance tuning, CUDA-based systems, and operating across cloud-native and hybrid environments (AWS, GCP, Azure). Salary & Benefits Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Equal Opportunity NVIDIA is committed to fostering a diverse work environment and 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. Applications for this job will be accepted at least until August 30, 2025.

JR2002881

Seniority level Mid-Senior level Employment type Full-time Job function Software Development Industries Computer Hardware Manufacturing Software Development Computers and Electronics Manufacturing #J-18808-Ljbffr NVIDIA

Job Tags

Full time, Remote work,

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