- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
- 8+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow
- Strong fundamentals in programming, optimizations, and software design, especially in Python
- Proficiency in problem-solving and debugging skills in GPU orchestration and Multi-Instance GPU (MIG) management within Kubernetes environments
- Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments
- Excellent knowledge of the theory and practice of LLM and DL inference
- Excellent presentation, communication and collaboration skills
Ways To Stand Out From The Crowd
- Prior experience with DL training at scale, deploying or optimizing DL inference in production
- Experience with NVIDIA GPUs and software libraries such as NVIDIA NIM, Dynamo, TensorRT, TensorRT-LLM
- Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design
- Familiarity with parallel programming and distributed computing platforms
#NALASAHiring
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 184,000 USD – 287,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.