Nvidia Senior Site Reliability Engineer Data Science ML Platforms 

United States, Texas 

774307007

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.