Working closely with customers to help them adopt and build creative solutions using NVIDIA technology and MLOps solutions
Analyzing performance and power efficiency of AI inference workloads on Kubernetes
Some travel to conferences and customers may be required (20%)
What We Need To See
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 the pay of employees in similar positions. The base salary range 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 September 20, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
