Deep Learning Performance Architect
NVIDIAJob Title
Deep Learning Performance Architect
Role Summary
Join NVIDIA's Deep Learning Architecture team to design and evaluate high-performance hardware and software for AI workloads. The role focuses on architecture, benchmarking, and tooling to improve parallel compute performance and energy efficiency.
Experience Level
Senior. The posting specifies at least 1+ years of experience with C, C++ and Python; the role is an architect-level position.
Responsibilities
Primary responsibilities include architecture development, workload analysis, and tooling for performance engineering.
- Design and evaluate hardware architectures to improve parallel compute performance and energy efficiency.
- Benchmark and analyze deep learning workloads in single-node and multi-node configurations.
- Develop profiling, analysis, and debugging tools for parallel applications using Python and C++.
- Collaborate with architecture teams and product management to guide product development.
- Monitor emerging trends and research in deep learning and performance engineering.
Requirements
Key qualifications and preferred skills.
- Must-have: 1+ years experience programming in C, C++ and Python.
- Must-have: Strong problem-solving skills and a curious mindset.
- Nice-to-have: Familiarity with GPU computing and parallel programming.
- Nice-to-have: Understanding of transformer-based model architectures.
- Nice-to-have: Experience with architecture simulator development, performance modeling, profiling, or analysis.
Education Requirements
B.Tech. or M.Tech. in Computer Science, Electrical Engineering, Mathematics, or a related discipline (explicitly listed in the posting).
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
