Senior Site Reliability Engineer, Data Science and ML Platforms

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Overview

The Senior Site Reliability Engineer for Data Science and Machine Learning Platforms at NVIDIA will play a crucial role in ensuring the reliability, availability, and performance of our data-driven initiatives. This position involves collaborating with cross-functional teams to enhance the infrastructure that supports our data science and machine learning workloads. The ideal candidate will utilize their expertise to implement automation, monitor system health, and resolve issues proactively, driving continuous improvements in systems performance and scalability.

Job Responsibilities

• Design, implement, and maintain scalable and robust systems to support data science and machine learning workflows.
• Develop and maintain monitoring, alerting, and incident response processes to ensure high availability of services.
• Automate operational tasks to improve efficiency and reduce human error.
• Collaborate with data scientists and engineers to optimize models and data pipelines.
• Perform root cause analysis and troubleshoot complex system issues across multiple components.
• Ensure compliance with security best practices and data governance policies.
• Lead post-mortem activities and implement lessons learned to prevent recurrence of incidents.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in site reliability engineering, DevOps, or related fields.
• Proficient in scripting languages such as Python, Bash, or Ruby.
• Strong experience with cloud platforms (AWS, Azure, or Google Cloud) and container orchestration technologies (Docker, Kubernetes).
• Deep understanding of networking and distributed systems.
• Experience with monitoring and observability tools such as Prometheus, Grafana, or Datadog.
• Familiarity with machine learning frameworks and data processing tools (TensorFlow, PyTorch, Apache Spark).
• Excellent problem-solving and analytical skills with a strong attention to detail.

Technologies & Tools

In this position, the Senior Site Reliability Engineer will utilize a diverse range of technologies and tools. Key systems include cloud infrastructures like AWS and Google Cloud, container management tools such as Docker and Kubernetes, as well as monitoring platforms like Prometheus and Grafana. Additionally, experience with machine learning frameworks, including TensorFlow and PyTorch, will be essential for optimizing data workflows and processes.

Ideal Candidates

The ideal candidate for this role will be a proactive and self-motivated individual with a strong drive for continuous improvement. They will exhibit exceptional communication skills to effectively collaborate with multidisciplinary teams and have a passion for technology and innovation. A successful Senior Site Reliability Engineer will demonstrate strong leadership qualities and a willingness to mentor junior team members, fostering an inclusive and knowledgeable work environment.