Cloud Scalability Engineer
2 weeks ago
In today's fast-paced business landscape, adaptability is crucial for success. We're seeking a skilled professional to help us develop scalable systems that can automatically adjust to fluctuating workloads, ensuring seamless performance and optimal resource utilization.
Our goal is to eliminate system crashes, downtime, and overspending on infrastructure. We want to create a system that can predict and adapt to real-time load, ensuring applications run smoothly regardless of traffic spikes.
For this master thesis, we'll be implementing and evaluating different scaling algorithms relevant to current studies and prior master theses. The focus will be on predicting oncoming load based on collected data and scaling the system accordingly. We'll also explore testing and comparing different load patterns and algorithms, including machine learning and frequency domain analysis.
The implemented algorithms will be evaluated and compared to industry-standard scaling algorithms in a cloud environment.
Key Responsibilities:- Design and implement predictive scaling algorithms
- Develop and evaluate different load patterns and algorithms
- Implement and test scalability solutions in a cloud environment
- Collaborate with our team to ensure seamless integration and performance
- Background in software engineering
- Experience with cloud-based applications and scalability
- Strong understanding of predictive modeling and simulation
- Excellent problem-solving and analytical skills
We're committed to providing a stimulating work environment and opportunities for growth and development. If you're passionate about scalability and efficiency, we encourage you to apply.
Please submit your resume and a personal letter explaining why you're interested in this opportunity.
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