Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples' lives.
We're looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you'll drive initiatives to optimize inference performance and scalability. You'll also be engaged in model design, to help assist our researchers in developing inference-friendly models.
This role is critical to scaling the team's broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation.
- Perform engineering efforts focused on improving model serving, inference performance, and system efficiency
- Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability
- Partner closely with research and product teams to ensure our models perform effectively at scale
- Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs
- Have deep expertise in model performance optimization, particularly at the inference layer
- Have a strong background in kernel-level systems, data movement, and low-level performance tuning
- Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads
- Can navigate ambiguity, set technical direction, and drive complex initiatives to completion
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
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