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Founding Member of Technical Staff, AI Infrastructure
Own the cross-layer path from a real customer workflow to private evaluation, agents, software, managed inference, and infrastructure decisions.
Careers ยท Build the whole path
Build useful AI systems. Follow the limits deeper.
Touchdown starts with real work: teach a team, deploy one useful system, manage what runs, and measure what breaks. We are building a small team across software, inference, kernels, hardware research, materials and manufacturing, and customer work.
These are focused application lanes, not rigid boxes. We care about evidence, learning speed, ownership, and the ability to connect your layer to the full system.
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Open roles.
Choose the lane closest to your work. If your experience crosses roles, select the closest one and explain the range in your application.
View role →
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Member of Technical Staff, Software Engineering
Build the product and operating software that turns technical capability into something people can use.
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Founding Inference Systems Engineer
Build the execution layer between a company AI workflow and the infrastructure that runs it.
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Founding Kernel Engineer, GPU Kernels
Turn measured AI-system bottlenecks into correctness-gated GPU kernel, precision, and memory-movement improvements.
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Member of Technical Staff, FPGA and Driver Systems
Build the verified bridge between host software, programmable logic, memory, and physical devices.
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Research Member of Technical Staff, Hardware Systems
Turn repeated software and infrastructure limits into hardware requirements, experiments, and defensible decisions.
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Research Member of Technical Staff, Materials and Manufacturing
Turn physical limits in compute into materials, process, reliability, and manufacturing research that can be qualified.
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GTM and Community Lead
Build demand in person: run the events, workshops, field programs, and follow-up that turn technical work into durable relationships.
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Member of Technical Staff Intern
Learn by shipping a bounded project across agents, software, systems, kernels, hardware, or technical education.
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What we look for.
Start with the work
Name the user, the problem, what breaks, and what a useful result changes.
Show the receipt
Connect claims to code, traces, experiments, measurements, shipped systems, or reviewed research.
Own the handoff
Make the work understandable, testable, and usable by the next person.
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Apply.
Send the clearest evidence of how you work. If uploads fail, email the same material to [email protected].