Used Tools & Technologies
Machine Learning HPCRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Go @ 4
Python @ 4
CI/CD @ 7
Distributed Systems @ 4
Data Engineering @ 7
Performance Optimization @ 7
API @ 4
CUDA @ 4
GPU @ 4
Observability @ 7
AI @ 4
Data Pipelines @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
At NVIDIA, we're solving the world's most exciting problems with our unique approach to accelerated computing. This role sits at the intersection of quantum computing, distributed systems, and advanced data platforms. You will help path-find the future of high-fidelity, real-time system modeling and co-design for quantum computing platforms.
Responsibilities
- Build and evolve scalable data platforms and interfaces that integrate heterogeneous system data, simulation outputs, AI model inputs/outputs, and application workflows.
- Design and implement agentic orchestration frameworks to support modeling, prediction, and coordination across complex computing systems.
- Develop synthetic data generation pipelines and supporting infrastructure for training, validation, and evaluation of AI-driven models.
- Implement robust data pipelines, storage systems, and APIs to support high-throughput, low-latency workloads across simulation and real-time environments.
- Collaborate closely with research and engineering teams to translate domain-specific models and system signals into performant, reliable systems.
Requirements
- BS, MS, or PhD in Computer Science, Engineering, Physics, or a related field (or equivalent experience).
- 10+ years of experience building and operating production-grade software systems, with strong fundamentals in data engineering and distributed systems.
- Working knowledge of quantum computing concepts and ability to collaborate effectively with domain experts.
- Hands-on experience with backend and data technologies (examples listed: Python, C++, Go, APIs, distributed services, and modern data platforms).
- Strong software engineering practices across testing, CI/CD, observability, and performance optimization.
Ways to stand out
- Experience building simulation or modeling platforms in scientific computing, physics, or hardware-software environments.
- Experience developing synthetic data pipelines or supporting AI/ML workflows at scale.
- Familiarity with agentic systems, orchestration frameworks, or AI-driven automation.
- Deeper exposure to quantum computing concepts, including hardware, control systems, or performance modeling.
- Experience with GPU acceleration, CUDA, or high-performance computing for large-scale workloads.
Compensation & Benefits
- Base salary ranges by level: Level 4: 184,000 USD - 287,500 USD; Level 5: 224,000 USD - 356,500 USD.
- You will also be eligible for equity and benefits (link to NVIDIA benefits referenced in the original posting).
Additional information
- Applications for this job will be accepted at least until July 4, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and committed to an inclusive work environment.