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As a Technical Lead Engineer, you will build an important liaison between our end users and their cameras. Consider the facility manager monitoring live video to keep their campus safe, the security guard investigating a historical incident, or the marketing manager reconfiguring their store layout based on foot traffic analysis; you’ll step into each user’s shoes, collaborating with our product and UX teams to craft intuitive and powerful tools to help our users find the answers and security they seek.
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As an
AI Infrastructure Abstraction Engineer, you will help shape the next generation of AI compute platforms by designing systems that abstract away hardware complexity and expose logical, scalable, and secure interfaces for AI workloads. Your work will enable multi-tenancy, resource isolation, and dynamic scheduling of GPUs and accelerators at scale — making infrastructure programmable, elastic, and developer-friendly.
You will bridge the gap between raw compute resources and AI/ML frameworks, allowing infrastructure teams and model developers to consume shared GPU resources with the performance and reliability of bare metal, but with the flexibility of cloud-native systems. Your contributions will empower internal and external users to run AI workloads securely, efficiently, and predictably — regardless of the underlying hardware topology.
This role is critical to enabling AI infrastructure that is multi-tenant by design, scalable in practice, and abstracted for portability across diverse platforms.
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Lead with Architecture and Outcomes

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