AI Infrastructure Performance & Modeling Lead

Renice AI; Mountain View (CA); Hybrid; USD 180,000 - 280,000; Full time

Job summary

Renice AI is seeking a Performance Lead to drive architecture decisions for AI inference workloads across the full system stack in Mountain View, CA. You will build modeling frameworks, analyze tradeoffs across compute, memory, networking, and storage, and translate results into actionable guidance for internal teams and hardware partners.

This role leads a small team of engineers, collaborates with ML, systems, and hardware groups, and shapes reference designs and long-term infrastructure

Qualifications

• Experience owning or building performance modeling frameworks used to drive real system design decisions.
• Deep knowledge of AI and machine learning workloads, including training and/or inference at scale.
• Understanding of system-level tradeoffs across compute, memory, and networking in large-scale distributed systems.
• Comfort working across abstraction layers, from workload behavior to hardware implementation.
• Experience using analytical modeling or simulation to inform architectural decisions.
• Ability to operate in ambiguous problem spaces and turn open-ended questions into structured analysis.
• Clear communication and the ability to influence internal teams and external partners.

Responsibilities

• Build and own a performance modeling framework and toolchain to evaluate AI systems across multiple levels of abstraction.
• Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology.
• Develop performance models to guide decisions on scale-up versus scale-out architectures, interconnect and network design, and memory hierarchy and system balance.
• Translate modeling outputs into clear recommendations for internal teams and external hardware vendors.
• Influence reference designs and vendor roadmaps through data-driven insights.
• Partner closely with machine learning, systems, and hardware teams to understand workload characteristics and requirements.
• Lead and grow a small team of two to three engineers, setting technical direction and maintaining high standards for modeling rigor.
• Continuously improve modeling fidelity by validating against real system behavior and measurements.

Skills

Performance modeling

AI workloads

System tradeoffs

Analytical modeling

Cross-functional communication

Job description

Renice AI is seeking a Performance Lead to drive architecture decisions for AI inference workloads across the full system stack in Mountain View, CA. You will build modeling frameworks, analyze tradeoffs across compute, memory, networking, and storage, and translate results into actionable guidance for internal teams and hardware partners.

This role leads a small team of engineers, collaborates with ML, systems, and hardware groups, and shapes reference designs and long-term infrastructure