Are you passionate about building and maintaining large-scale production systems that support advanced data science and machine learning applications? Do you want to join a team at the heart of NVIDIA's data-driven decision-making culture? If so, we have a great opportunity for you! NVIDIA is seeking a Senior Site Reliability Engineer (SRE) for the Data Science & ML Platform(s) team. The role involves designing, building, and maintaining services that enable real-time data analytics, streaming, data lakes, observability and ML/AI training and inferencing. The responsibilities include implementing software and systems engineering practices to ensure high efficiency and availability of the platform, as well as applying SRE principles to improve production systems and optimize service SLOs. Additionally, collaboration with our customers to plan implement changes to the existing system, while monitoring capacity, latency, and performance is part of the role.
To succeed in this position, a strong background in SRE practices, systems, networking, coding, capacity management, cloud operations, continuous delivery and deployment, and open-source cloud enabling technologies like Kubernetes and OpenStack is required. Deep understanding of the challenges and standard methodologies of running large-scale distributed systems in production, solving complex issues, automating repetitive tasks, and proactively identifying potential outages is also necessary. Furthermore, excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential. As a Senior SRE at NVIDIA, you will have the opportunity to work on innovative technologies that power the future of AI and data science, and be part of a dynamic and supportive team that values learning and growth. The role provides the autonomy to work on meaningful projects with the support and mentorship needed to succeed, and contributes to a culture of blameless postmortems, iterative improvement, and risk-taking. If you are seeking an exciting and rewarding career that makes a difference, we invite you to apply now!
What you’ll be doing:
Develop software solutions to ensure reliability and operability of large-scale systems supporting machine-critical use cases.
Gain a deep understanding of our system operations, scalability, interactions, and failures to identify improvement opportunities and risks.
Create tools and automation to reduce operational overhead and eliminate manual tasks.
Establish frameworks, processes, and standard methodologies to enhance operational maturity, team efficiency, and accelerate innovation.
Define meaningful and actionable reliability metrics to track and improve system and service reliability.
Oversee capacity and performance management to facilitate infrastructure scaling across public and private clouds globally.
Build tools to improve our service observability for faster issue resolution.
Practice sustainable incident response and blameless postmortems
What we need to see:
Minimum of 5-8 years of experience in SRE, Cloud platforms, or DevOps with large-scale microservices in production environments.
Master's or Bachelor's degree in Computer Science or Electrical Engineering or CE or equivalent experience.
Strong understanding of SRE principles, including error budgets, SLOs, and SLAs.
Proficiency in incident, change, and problem management processes.
Skilled in problem-solving, root cause analysis, and optimization.
Experience with streaming data infrastructure services, such as Kafka and Spark.
Expertise in building and operating large-scale observability platforms for monitoring and logging (e.g., ELK, Prometheus).
Proficiency in programming languages such as Python, Go, Perl, or Ruby.
Hands-on experience with scaling distributed systems in public, private, or hybrid cloud environments.
Experience in deploying, supporting, and supervising services, platforms, and application stacks.
Ways to stand out from the crowd:
Experience operating large-scale distributed systems with strong SLAs.
Excellent coding skills in Python and Go and extensive experience in operating data platforms.
Knowledge of CI/CD systems, such as Jenkins and GitHub Actions.
Familiarity with Infrastructure as Code (IaC) methodologies and tools.
Excellent interpersonal skills for identifying and communicating data-driven insights.
NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.
