Staff Systems Engineer, AI/ML

Job Title

Staff Systems Engineer, AI/ML

Role Summary

Senior individual contributor who leads workload-driven architecture strategy across hardware and software boundaries for AI/ML systems. Owns workload characterization, performance modeling, and cross-functional alignment to inform SoC, memory subsystem design, and HW/SW co-optimization.

This is a 100% in-office role with positions in Dallas, Austin, or San Jose; the role communicates findings to senior engineering and product stakeholders.

Experience Level

Senior — expects 4+ years of industry experience in systems engineering, hardware architecture, ML systems, or performance engineering.

Responsibilities

Primary responsibilities include workload characterization, performance analysis, modeling, and communicating recommendations.

• Lead end-to-end workload characterization and hardware performance analysis for AI/ML systems: workload selection, measurement methodology, and analytical modeling.
• Drive architectural discussions across CPU, SoC, memory, interconnect, compilers, runtimes, and ML framework teams.
• Define and maintain a performance KPI framework: metrics, measurement methods, pre-silicon estimation, and decision criteria for architecture tradeoffs.
• Identify bottlenecks (compute, DRAM/LPDDR bandwidth, on-chip memory capacity, data movement latency, software overhead) and recommend architectural changes or optimization investments.
• Mentor and train junior engineers in performance modeling and workload-driven design methods.
• Present concise recommendations and detailed technical analysis to senior engineering leadership and product stakeholders.
• Perform work in a safe manner and support Environmental, Health, Safety & Security programs.

Requirements

Must-have technical skills and attributes; preferred items noted where applicable.

• Proven ability to derive and defend analytical performance models (roofline, bandwidth-latency, first-principles throughput) and reason about quantized and sparse model behavior.
• Deep expertise in CPU and SoC architecture, memory hierarchies, out-of-order execution, and vector/SIMD pipelines.
• Strong command of system-level memory bandwidth considerations (DDR/LPDDR bandwidth, channel configuration, utilization) and quantitative reasoning about compute-bound vs memory-bound workloads.
• Experience with AI/ML acceleration on edge devices (NPUs, inference accelerators, DSP-based pipelines) and HW/SW co-design challenges.
• Familiarity with AI compiler infrastructure (MLIR, IREE, TVM or equivalent) is preferred and improves effectiveness with software teams.
• Demonstrated technical leadership, strong written and verbal communication, and ability to influence cross-functional teams without direct authority.
• English fluency (written & verbal); travel up to 10%.
• On-site presence required in one of the U.S. offices (Dallas, Austin, or San Jose).
• Reasonable accommodation requests: contact usaccommodations@gf.com.

Education Requirements

Bachelor's or Master's degree (MS preferred) in Electrical Engineering, Computer Engineering, Computer Science, or equivalent; or equivalent practical experience.

About the Company

Company: GlobalFoundries

Headquarters: Saratoga Springs, New York, USA

GlobalFoundries is a leading contract manufacturer for the global semiconductor industry, with facilities in multiple countries, including the USA. The company develops a broad portfolio of semiconductor technologies and employs around 13,000 people worldwide. GlobalFoundries focuses on enhancing competitiveness in specialized application solutions and fostering innovation in mobile communications, consumer electronics, and automotive applications.