At Hark, we are building the most advanced personal intelligence in the world.
About the role
We are looking for a Member of Technical Staff, Infrastructure Compute to lead and manage large-scale GPU computing clusters powering our AI training and deployment workloads. You'll work at the intersection of systems engineering and machine learning infrastructure, owning the reliability, scalability, and efficiency of the compute platform that our research and engineering teams depend on.
What they're looking for
- 5+ years of experience in infrastructure, systems, or platform engineering, with at least 2 years working in ML or HPC environments
- Demonstrated experience managing GPU clusters or large-scale distributed compute infrastructure
- Strong proficiency in at least one systems or infrastructure programming language
- Deep understanding of networking fundamentals (RDMA, InfiniBand, or RoCE a plus) relevant to high-throughput training workloads
- Experience with container orchestration, job scheduling, and multi-tenant resource management
- Proven track record owning production systems with high reliability requirements
More about this role
Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.
We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.
To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.
We are looking for a Member of Technical Staff, Infrastructure Compute to lead and manage large-scale GPU computing clusters powering our AI training and deployment workloads. You'll work at the intersection of systems engineering and machine learning infrastructure, owning the reliability, scalability, and efficiency of the compute platform that our research and engineering teams depend on. This is a high-impact, highly technical role suited for someone who thrives in complex...
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