Title:  Performance Analysis Engineer

Job Summary

As a Performance Analysis engineer, you will work as part of a team responsible for modeling, measurement, and analysis of storage systems performance. The overall focus of the Research and Development function, of which this role is a part, is on competitive market and customer requirements, technology advances, product quality, product cost and time to market. 

Performance engineers focus on performance analysis and improvement for new products and features as well as enhancements to existing products and features. This position requires an individual to be broad-thinking and systems-focused, creative, team-oriented, technologically savvy, and driven to produce results.
 
•    Measure and analyze product performance to identify performance improvement opportunities.
•    Design, implement, execute, analyze, interpret, socialize and apply storage-oriented performance workloads and their results, including the creation of tools and automation as necessary.
•    Work closely with development teams to drive the performance improvement agenda.
•    Evaluate design alternatives for enhanced performance and prototype opportunities for performance enhancements.
•    Create analytical and simulation-based models to predict storage systems performance.
•    Successfully convey information to stakeholders at many levels related to the position.
•    Participate as a proactive contributor and subject matter expert on team projects.
 

Job Requirements

•    Knowledge of performance analysis and modeling techniques, tools and benchmarking.
•    Extensive knowledge and experience in computer operating systems, hardware architecture and design, data structures and standard programming practices; systems programming in C is highly desirable.
•    Strong scripting skills (Perl, python - primarily with Jupyter notebooks, shell).
•    Exceptional presentation and interpersonal skills.
•    Strong influencing and leadership skills. 
•    The ability to make accurate work estimates and develop predictable plans.
•    A creative and analytical approach to problem-solving.
•    Knowledge of storage and file systems.
•    Understanding of AI/ML workloads.
•    Understanding of performance tradeoffs when designing on-prem and cloud systems.
•    The ability and willingness to adapt to rapidly changing work environments, and enhance automation frameworks (generally python-based) to improve productivity.
 

Education

•    8 to 10 years of experience is preferred.
•    A Bachelor of Science, Master’s of Science, or PhD Degree in Electrical Engineering or Computer Science; or equivalent experience is required.