Job description

NVIDIA is a world-leader in Gaussian Splatting and Neural reconstruction. Our team builds the Omniverse NuRec SDK to enable robotic, healthcare, and AV developers to build better models faster with closed-loop validation and closed-loop training grounded in real-world scenarios. Are you fascinated by the latest developments in Vision Language Models and 3D reconstruction? We are looking for a driven Software Engineer to bring ground breaking models into NVIDIA's software ecosystem for neural graphics to improve its robustness and accuracy and enrich its capabilities. Your software will help bridge the gap between the real world and simulations. Join our amazing team and help us build the future of Physical AI! What you'll be doing: • Design, build, and optimize containerized inference execution for the latest 3D VLMs from NVIDIA, turning research work into production-grade, highly optimized software (NIMs, NVIDIA Inference Microservices) • Develop benchmarks to validate the models accuracy and performance (latency, throughput, scalability) • Release and maintain the models and their pipelines throughout their lifecycle (bug fixes, security patches) • Contribute VLM-related features to Open-Source projects like vLLM • Collaborate closely with Research and Product teams and influence our common roadmaps What we need to see: • Master's of Science in Computer Science + 3 years, or Electrical Engineering, Bachelor of Science (or equivalent experience) + 5 years of experience. • History of building, validating and releasing production-grade AI distributed systems, backend services, microservices, and cloud technologies. • Deep technical expertise in distributed applications using Docker, Kubernetes, endpoints and their APIs (REST, gRPC), Helm. • Hands-on experience with modern inference platforms (vLLM, SGLang, Torch, TRT, TRT-LLM). • Proficiency with Python and C++. • Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization). • Excellent written, visual, and verbal communication. • Curiosity and drive to learn new technologies and partner across teams and functions. Ways to Stand Out from the Crowd: • Track record contributing to open-source or production-grade software. Are you a vLLM contributor already? • Experience with ML model engineering: training, fine-tuning, distillation, quantization. • Experience with low-level optimization of ML models (CUDA kernels) • Strong fundamentals in 3D graphics, 3D computer vision or neural reconstruction (NERFs, Gaussian Splats). • History of multidisciplinary creativity and innovation around software engineering in multiple problem domains. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until May 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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.

Requirements

Must-haves

Design, build, and optimize containerized inference execution for the latest 3D VLMs from NVIDIA, turning research work into production-grade, highly optimized software (NIMs, NVIDIA Inference Microservices)
Develop benchmarks to validate the models accuracy and performance (latency, throughput, scalability)
Release and maintain the models and their pipelines throughout their lifecycle (bug fixes, security patches)
Contribute VLM-related features to Open-Source projects like vLLM
Collaborate closely with Research and Product teams and influence our common roadmaps
Master's of Science in Computer Science + 3 years, or Electrical Engineering, Bachelor of Science (or equivalent experience) + 5 years of experience.
History of building, validating and releasing production-grade AI distributed systems, backend services, microservices, and cloud technologies.
Deep technical expertise in distributed applications using Docker, Kubernetes, endpoints and their APIs (REST, gRPC), Helm.
Hands-on experience with modern inference platforms (vLLM, SGLang, Torch, TRT, TRT-LLM).
Proficiency with Python and C++.
Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization).
Excellent written, visual, and verbal communication.
Curiosity and drive to learn new technologies and partner across teams and functions.
Track record contributing to open-source or production-grade software. Are you a vLLM contributor already?
Experience with ML model engineering: training, fine-tuning, distillation, quantization.
Experience with low-level optimization of ML models (CUDA kernels)
Strong fundamentals in 3D graphics, 3D computer vision or neural reconstruction (NERFs, Gaussian Splats).
History of multidisciplinary creativity and innovation around software engineering in multiple problem domains.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until May 2, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aidockerkubernetesrestllmpythonci/cdml

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

Vision