Used Tools & Technologies
Not specified
Required 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.
DevOps @ 4
Python @ 4
Machine Learning @ 4
JavaScript @ 4
API @ 4
LLM @ 4
Cloud Computing @ 4
GPU @ 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
NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities which are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence.
NVIDIA is seeking top-tier Senior Deep Learning Infrastructure Engineers. In this role, you will play a crucial part in building the deep learning infrastructure that powers our AI agents for VLSI design, driving innovation and efficiency in chip development. Join us in a dynamic, professional, and growth-oriented environment where your expertise will have a significant impact on the future of technology.
Responsibilities
- Build applications and develop infrastructure for a highly scalable deep learning platform.
- Design, build, and maintain high-bandwidth data pipelines and related infrastructure, such as APIs, databases, and services.
- Work closely with domain experts and research teams; take ownership of productizing, releasing, and maintaining deep learning products.
- Act as an engineering generalist: discover and build skills needed at different times to solve the problems at hand.
Requirements
- Bachelor’s/Master's degree in computer science, engineering, or related field (or equivalent experience).
- Minimum 6+ years of experience in services, pipelines, API development, and system design.
- Expertise in Python, JavaScript, or another similar programming language.
- Zeal to learn and perform beyond prior experience and expertise.
Ways to stand out
- Experience in DevOps, full-stack development, databases, and cloud computing.
- Fundamentals in machine learning and experience building RAG pipelines or other LLM applications.
Compensation & Benefits
- 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.
Additional information
- Applications for this job will be accepted at least until January 24, 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 is proud to be an equal opportunity employer.