AI Architecture and Systems Engineering

Location: Palo Alto, United States; hybrid

Salary: $180,000–$220,000 per year

Company

hirify.global is building operator intelligence infrastructure for industrial hardware programs, with a unified foundation model already deployed in semiconductor and hardware environments.

What you will do

• Design and refine transformer variants for structured spatial domains, including sparse, locality-aware, hierarchical, and graph-transformer architectures.
• Scale distributed training beyond 45TB datasets while improving generalization, curriculum strategies, reproducibility, and deterministic execution.
• Architect inference systems for trillion-voxel domains by balancing memory, computation, communication, throughput, and stability.
• Expand operator capabilities across Maxwell’s equations, elasticity, plasticity, Navier–Stokes, nonlinear constitutive systems, and coupled multiphysics interactions.
• Ship production AI capabilities for Tier-1 hardware programs and support multi-entity industrial deployments.

Requirements

• Deep experience with large-scale foundation model architecture and transformer variants.
• Experience building distributed training systems, production ML systems, and scalable structured-data pipelines.
• Strong software engineering fundamentals with clean, maintainable, scalable code.
• Experience with modern ML stacks such as PyTorch and distributed training ecosystems.
• Strong CI, regression testing, validation, reproducibility, and determinism discipline.
• Experience building AI systems that run in production rather than only in experimental environments.

Culture & Benefits

• Work on production infrastructure rather than a research prototype.
• High ownership at a Series A stage.
• Opportunity to define a foundational abstraction layer early.
• Work with a model trained on 45TB+ of structured physics data and deployed in Tier-1 hardware workflows.
• Success is measured by industrial adoption, throughput, and reliability.