Tech Stack
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.
AI @ 3
Algorithms @ 3
Cloud Computing @ 6
Distributed Systems @ 6
GPU @ 3
Machine Learning
Networking @ 6
Python @ 3
- 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
Today, NVIDIA is 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 NVIDIA, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.
We are now looking for a Research Scientist New Graduate with a focus on Machine Learning Systems (MLSys). NVIDIA Research is seeking exceptional systems researchers to contribute to the development of hardware, software, and infrastructure technology for ML systems of all scales. Advances in AI/ML heavily rely on the development of efficient, scalable, resilient, and trustworthy systems for training, fine-tuning, and serving ML models. AI/ML applications are also pushing the limits of both personal devices and warehouse-scale data centers. All layers of AI systems need to be co-designed and co-optimized to maximize performance and energy efficiency, improve scalability, and support emerging algorithms in this space.
Responsibilities
- Understand and analyze the efficiency, scaling, and resilience challenges in ML systems, algorithms, and applications.
- Develop creative systems solutions (hardware, software, infrastructure) for future ML systems of all scales.
- Contribute to the co-design of next-generation AI/ML algorithms and systems.
- Collaborate with a diverse set of research and product teams across the company, spanning software, hardware, AI, and networking.
- Publish original research and speak at conferences and events.
Requirements
- Recent graduate with a Ph.D. in CS/CE/EE with a strong background in operating systems, distributed systems, inference and training systems, data management systems, networking, cloud computing, and/or computer architecture (or equivalent experience). A strong publication, patent, and research collaboration history is a huge advantage.
- Demonstrated expertise in one specific area with the ability to become the go-to resource within a team having varied backgrounds.
- Background with experimental research and development.
- Experience with C, C++, Python, and/or scripting languages.
- Experience with using AI tools for analysis, design, and code development.
Salary
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD.
You will also be eligible for equity and benefits.