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Performance Engineer (Cloud Data Plane Engineering)

NetApp, Inc.
Posted 3 months ago, valid for 13 days
Location

San Jose, CA 95138, US

Salary

$147,900 - $220,000 per year

Contract type

Full Time

Health Insurance
Retirement Plan
Paid Time Off
Life Insurance

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Sonic Summary

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  • This job involves designing, developing, and optimizing cloud software and performance capabilities for cloud storage services and distributed systems.
  • The ideal candidate should have a minimum of 4 years of experience in performance analysis and modeling techniques, along with knowledge of AI/ML applications in performance engineering.
  • Responsibilities include executing performance benchmarks, applying AI-assisted techniques, and analyzing customer experience signals to identify improvement opportunities.
  • The target salary range for this position is between 147,900 and 220,000 USD, with final compensation influenced by the candidate's qualifications and location.
  • A Bachelor’s, Master’s, or PhD in Electrical Engineering or Computer Science is required, along with strong programming skills, particularly in C and Python.

Job Summary

Design, develop, analyze, and optimize cloud software and performance capabilities for cloud storage services and distributed systems. In this role you will collaborate with cross-functional engineering teams to model, measure, analyze, and improve the performance, scalability, and cost-efficiency of cloud platforms—ensuring customer and market requirements are met while balancing quality, cost, and time-to-market. The ideal candidate is systems-focused, analytical and creative, and driven to deliver measurable performance improvements at cloud scale.

Responsibilities

  • Design and execute performance benchmarks/workloads; measure, analyze, interpret, and socialize results to identify improvement opportunities.
  • Apply AI-assisted performance engineering techniques and develop tools (e.g., performance analysis, automated regression triage, and ML-based capacity planning) to accelerate bottleneck analysis and guide optimization priorities.
  • Evaluate design alternatives and prototype performance enhancements across cloud services and distributed components.
  • Collect and analyze customer experience signals and usage patterns; prepare findings and recommendations for engineering and management. 

Job Requirements

  • A minimum of 4 years of experience is required.
  • Knowledge of performance analysis, modeling techniques, benchmarking, and workload characterization.
  • Understanding of performance tradeoffs when designing for multi-tenant, elastic cloud environments (latency, throughput, cost, and reliability).
  • Hands-on experience applying AI/ML techniques to performance engineeringUnderstanding of AI/ML workloads and their impact on cloud storage performance.
  • Strong foundations in operating systems, data structures, and standard programming practices; systems programming in C is highly desirable.
  • Proficiency with scripting and automation (Python, shell; Perl acceptable) and comfort working with notebooks (e.g., Jupyter). 

Education

  • A Bachelor of Science, Master of Science, or PhD Degree in Electrical Engineering or Computer Science; or equivalent experience is required. 

Compensation:
The target salary range for this position is 147,900 - 220,000 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU’s), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. 




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