Amazon Power Performance Software Engineer Annapurna Labs 

United States, Texas, Austin 

313052735

Key job responsibilities
- Develop and automate tools and frameworks for running training and inference workloads, as well as collecting power and performance metrics.
- Use programming and scripting languages (C/C++, Python, Bash, etc.) to create efficient workflows for automating the execution of complex workloads and data collection processes.
- Perform in-depth data analysis of collected power and performance metrics, identifying key trends, bottlenecks, and opportunities for optimization.- Build and maintain interactive dashboards and data visualization tools to communicate insights from performance and power data clearly and effectively to technical and non-technical stakeholders.
- Contribute to the creation of end-to-end automated pipelines for continuous power and performance testing, monitoring, and reporting.
- Design and implement data validation processes to ensure the accuracy and integrity of collected power and performance metrics across various workloads.
- Perform root cause analysis of performance and power inefficiencies, using custom scripts and tools to debug and optimize system-level performance.
- Optimize data collection and analysis processes to improve efficiency, scalability, and accuracy in high-performance environments.- Stay current on emerging tools, technologies, and best practices in power and performance analysis, contributing to the evolution of our tool set and frameworks.
Diverse Experiences
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Mentorship & Career Growth
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- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Strong experience in programming and scripting (Python, Bash, or similar) to automate data collection, analysis, and reporting tasks.
- Proficiency in developing and maintaining custom tools for power and performance measurement in data center environments.
- Experience with data analysis frameworks (e.g., Pandas, NumPy) and data visualization tools (e.g. Matplotlib, Power BI, Tableau) to analyze and present performance data.
- Strong background in automating system-level performance testing and benchmarking.

- Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and related workloads.
- Familiarity with power management techniques such as dynamic voltage and frequency scaling (DVFS), low-power states, and energy-efficient design.
- Experience with developing automated testing pipelines for continuous integration of power and performance metrics.
- Strong problem-solving skills and the ability to debug complex power and performance issues in large-scale systems.