Used Tools & Technologies
Machine LearningRequired 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.
Docker @ 4
Go @ 3
Kubernetes @ 4
DevOps @ 4
Python @ 3
GCP @ 3
AWS @ 3
Azure @ 3
Bash @ 3
Communication @ 4
Networking @ 4
PyTorch @ 4
Cloud Computing @ 3
GPU @ 4
AI @ 4
InfiniBand @ 4
Slurm @ 4
HPC @ 8
JAX @ 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
We are seeking a Principal AI and ML Infra Software Engineer, GPU Clusters at NVIDIA to join our Hardware Infrastructure team. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!
Responsibilities
- Engage closely with AI and ML research teams to discern their infrastructure requirements and barriers, converting those insights into actionable improvements.
- Proactively identify researcher efficiency bottlenecks and lead initiatives to systematically improve them; drive the direction and long-term roadmaps for such initiatives.
- Monitor and optimize the performance of infrastructure ensuring high availability, scalability, and efficient resource utilization.
- Help define and improve important measures of AI researcher efficiency, ensuring that actions are in line with measurable results.
- Work closely with a variety of teams, such as researchers, data engineers, and DevOps professionals, to develop a cohesive AI/ML infrastructure ecosystem.
- Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.
Requirements
- BS or similar background in Computer Science or related area (or equivalent experience).
- 15+ years of demonstrated expertise in AI/ML and HPC tasks and systems.
- Hands-on experience using or operating High Performance Computing (HPC) grade infrastructure and in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., InfiniBand, RoCE, Amazon EFA), and container technologies (Docker, Enroot).
- Capability in supervising and improving substantial distributed training operations using PyTorch (DDP, FSDP), NeMo, or JAX; in-depth understanding of AI/ML workflows, including data processing, model training, and inference pipelines.
- Proficiency in programming & scripting languages such as Python, Go, Bash; familiarity with cloud computing platforms (e.g., AWS, GCP, Azure); experience with parallel computing frameworks and paradigms.
- Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
- Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds.
Benefits
- NVIDIA offers competitive salaries and a comprehensive benefits package.
- You will also be eligible for equity and benefits (see NVIDIA benefits page).
- Base salary range: 272,000 USD - 431,250 USD.
Additional information
- Applications for this job will be accepted at least until May 1, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.