Senior Performance & Systems Architect

Description About the Role Majestic Labs builds power-efficient AI servers for the largest and most advanced AI workloads. We are looking for a Senior Architect to work on simulation and translating architectural ideas into quantitative, defensible performance models. This role is ideal for someone who lives at the intersection of: Computer architecture Workload characterization System-level modeling AI / data-intensive workloads What You’ll Do Performance simulator & translate workloads into models Extend and maintain system-level performance models (compute, memory, interconnect, scheduling). Model system behaviors: NUMA effects, contention, coherence, bandwidth saturation. Characterize real workloads (LLMs, GNNs, graph analytics, tabular models and more). Guide architectural decisions Evaluate architectural trade-offs Produce quantitative comparisons vs. existing and emerging AI platforms. Work closely with hardware architects, compiler/runtime teams, and external partners. Ensure simulator assumptions align with hardware and software reality. Support external conversations Contribute to technical deep dives with strategic partners and customers. Help translate performance modeling into clear narratives for execs and investors. Requirements What We’re Looking For Required BSc in CS, EE, CE or similar degrees plus 8 years experience in computer architecture, systems research, or performance engineering. Or PhD in CS, EE, CE or similar degrees plus 2 years of relevant experience. Strong background in performance modeling or simulation (analytical, event-driven). Experience with AI or graph workloads. Understanding of: memory hierarchies (NUMA, caches, coherence), Interconnects (PCIe, fabrics, RDMA-), GPU-based systems. Hands-on coding experience (Python, C/C++, or similar). Ability to reason from first principles, not just benchmarks. Strong Plus Background in architecture simulators ( gem5-like, in-house tools, or research frameworks). Exposure to ML runtimes, compilers, or hardware-aware model design. Research background (MS/PhD) in computer systems (CS/EE), architecture, or related fields.