Redefining Robotic Intelligence. Backed by Khosla.
About the role
Our foundation world models have to run fast enough to control robots in the real world, and efficiently enough to support large-scale research. As an Inference Infrastructure Engineer Intern, you'll work with our infra and research engineers to make model inference faster and more efficient across the stack, from data pipelines down to GPU kernels. You'll own a scoped, high-impact project end to end, ship it into our production or research workflow, and present your results to the team. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Data efficiency optimization: experience speeding up data loading and preprocessing pipelines (especially video or other high-bandwidth sensor data), cutting IO and memory overhead, or improving data/compute utilization in ML systems
- GPU kernel optimization: experience writing or tuning GPU kernels in CUDA, Triton, CUTLASS, or similar, familiarity with the GPU memory hierarchy, occupancy, and profiling tools (Nsight Systems/Compute, PyTorch profiler)
- Currently pursuing a BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field
- Strong programming skills in Python and/or C++
- Solid understanding of deep learning fundamentals and at least one framework (PyTorch preferred)
More about this role
At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.
Our foundation world models have to run fast enough to control robots in the real world, and efficiently enough to support large-scale research. As an Inference Infrastructure Engineer Intern, you'll work with our infra and research engineers to make model inference faster and more efficient across the stack, from data pipelines down to GPU kernels. You'll own a scoped, high-impact project end to end, ship it into our production or research workflow, and present your results to the team.
Profile and benchmark inference for large video and world models to...
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