Predictive Maintenance Intern, Python

March 15

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SonicWall

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About SonicWallSonicWall has been fighting the cyber-criminal industry for over 30 years defending small, medium-size businesses and enterprises worldwide. Backed by research from the Global Response Intelligent Defense (GRID) Threat Network, our award-winning real-time breach detection and prevention solutions, coupled with the formidable resources of over 10,000 loyal channel partners around the globe, are the backbone securing more than a million business and mobile networks and their emails, applications and data. This combination of products and partners has enabled a real-time cyber defense solution tuned to the specific needs of the more than 500,000 global businesses in more than 215 countries and territories.Originally founded in 1991.*U.S. Patents 7,310,815; 7,600,257; 7,738,380; 7,835,361; 7,991,723

firewall • ngfw • application intelligence and control • network security

1001 - 5000 employees

Founded 1991

📋 Description

• We are looking for a motivated and enthusiastic intern to join our Engineering team and gain hands-on experience in software development in public cloud environment. • As an intern, you will have the opportunity to research and build autonomous systems in predictive maintenance by applying statistical methods and AI/ML techniques. • Predictive Maintenance: Using AI to optimize Reliability of cloud workloads. • Reliability of a system that is deployed in cloud infrastructure is often impacted by failures, security vulnerabilities or scalability issues due to contention or issues with resource utilization. • The effects are degraded performance, unplanned downtime, adverse effect on resource usage and cost, and unsatisfactory user experience. Predictive maintenance is a proactive maintenance strategy to help identify potential issues before they escalate into major problems and prescribing solutions to address them proactively. • The objective of this research is to collect historical and real-time, time-series data of metrics/traces/logs of cloud workloads from cloud infrastructure monitoring and APM services and use statistical methods and AI/ML techniques to analyze the data to predict when the system would fail to meet reliability objectives and recommend solutions to address them proactively. • Key Responsibilities: Data collection and preparation of metrics/traces/logs data from cloud infrastructure monitoring/APM services for data analysis, Develop and deploy time-series forecasting models for real-time predictions to optimize reliability of cloud workloads, Conduct research on the relevant topics and present to the team.

🎯 Requirements

• Currently pursuing a Bachelors/Masters degree in statistical computing/data science/computer science. • Detail oriented and must have excellent analytical skills • Must have Knowledge in Python. • Knowledge of AI/ML frameworks (TensorFlow, PyTorch, Keras) is a plus. • Excellent communication and organizational skills. • Ability to work as part of a team.