Software Engineer (AI/ML Performance)

Location: Hybrid role in Morrisville, North Carolina, United States, with in-office and/or in-person expectations.

Salary: $147,900–$220,000 per year, with final compensation based on location, qualifications, experience, and education.

Company

Enterprise data infrastructure provider delivering cloud storage, integrated data services, and solutions for AI and multicloud environments.

What you will do

• Design and execute performance benchmarks and workloads, then measure, analyze, interpret, and communicate results.
• Develop AI-assisted performance engineering tools for performance analysis, automated regression triage, and ML-based capacity planning.
• Evaluate design alternatives and prototype performance improvements across cloud services and distributed components.
• Analyze customer experience signals and usage patterns to prepare recommendations for engineering and management.
• Improve the performance, scalability, and cost-efficiency of cloud platforms while balancing latency, throughput, reliability, quality, and time-to-market.

Requirements

• At least 4 years of professional experience.
• Knowledge of performance analysis, modeling, benchmarking, and workload characterization.
• Understanding of performance tradeoffs in multi-tenant, elastic cloud environments.
• Hands-on experience applying AI and machine learning techniques to performance engineering and understanding their impact on cloud storage performance.
• Foundations in operating systems, data structures, and standard programming practices; systems programming in C is highly desirable.
• Proficiency with Python, shell scripting, automation, and notebooks such as Jupyter; a bachelor's, master's, or PhD degree in Electrical Engineering or Computer Science, or equivalent experience.

Culture & Benefits

• Hybrid working environment with in-office and in-person collaboration expectations.
• Health insurance, life insurance, retirement or pension plans, paid time off, and leave options, subject to regional policies.
• Performance-based incentives, employee stock purchase plan, and possible restricted stock units.
• Flexible environment supporting professional and personal balance.
• Inclusive culture focused on initiative, impact, ownership, and problem-solving.

Hiring process

• Applications are reviewed only when submitted through the company website.
• Some stages of the process may use AI tools to support application evaluation and candidate selection.