Senior Site Reliability Engineer, Data Science and ML Platforms
2 months ago
Senior Site Reliability Engineer, Data Science and ML Platforms
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.
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.
The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits.
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.
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