NVIDIA is looking for a Senior Site Reliability Engineer to join our AI Infrastructure Production Engineering team. You will be responsible for developing and maintaining large-scale systems supporting critical use cases for AI Infrastructure, driving reliability, operability, and scalability across global public and private clouds.
What You'll Do
- Develop and maintain large-scale systems supporting critical use cases for AI Infrastructure, driving reliability, operability, and scalability across global public and private clouds.
- Implement SRE fundamentals, including incident management, monitoring, and performance optimization, while designing automation tools to reduce manual processes and operational overhead.
- Build tools and frameworks to improve observability, define actionable reliability metrics, and enable fast issue resolution, driving continuous improvement in system performance.
- Establish frameworks for operational maturity, lead sustainable incident response protocols, and conduct blameless postmortems to improve team efficiency and system resilience.
- Work with engineering teams to deliver innovative solutions, mentor peers, uphold high standards for code and infrastructure, and contribute to hiring for a diverse, high-performing team.
What We're Looking For
- Degree in Computer Science or related field, or equivalent experience with 8+ years in Software Development, SRE, or Production Engineering.
- Proficiency in Python and at least one other language (C/C++, Go, Perl, Ruby).
- Expertise in systems engineering within Linux or Windows environments and cloud platforms (AWS, OCI, Azure, GCP).
- Strong understanding of SRE principles, including error budgets, SLOs, SLAs, and Infrastructure as Code tools (e.g., Terraform CDK).
- Hands-on experience with observability platforms (e.g., ELK, Prometheus, Loki) and CI/CD systems (e.g., GitLab).
- Strong communication skills with the ability to convey technical concepts effectively to diverse audiences.
- Commitment to fostering a culture of diversity, curiosity, and continuous improvement.
Nice to Have
- Experience in AI training, inferencing, and data infrastructure services.
- Proficiency in deep learning frameworks like PyTorch, TensorFlow, JAX, and Ray.
- A strong background in hardware health monitoring and system reliability.
- Hands-on expertise in operating and scaling distributed systems with stringent SLAs, ensuring high availability and performance.
- Proven experience in incident, change, and problem management processes, fostering continuous improvement in sophisticated environments.
Technical Stack
- Languages: Python, C/C++, Go, Perl, Ruby
- Systems: Linux, Windows
- Clouds: AWS, OCI, Azure, GCP
- Infrastructure Tools: Terraform CDK, ELK, Prometheus, Loki, GitLab
- AI/ML Frameworks: PyTorch, TensorFlow, JAX, Ray
Team & Environment
You will join NVIDIA's AI Infrastructure Production Engineering team, a diverse and encouraging environment where everyone is inspired to do their best work.
Benefits & Compensation
- Compensation Range: $184,000 USD - $287,500 USD for Level 4, and $224,000 USD - $356,500 USD for Level 5.
- Equity eligibility.
- Comprehensive benefits package.
NVIDIA is committed to fostering a diverse 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.
