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Inference

Genesis· Engineering & Research
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Bay AreaFull-timePosted 5mo ago

About the role

Build and optimize low-latency inference pipelines for on-device deployment and distributed GPU clusters; develop tools and low-level code to ensure real-time performance, reliability, and scalability in robotics and related workloads.

Responsibilities

  • Build low-latency inference pipelines for on-device deployment, enabling real-time next-token and diffusion-based control loops in robotics
  • Design and optimize distributed inference systems on GPU clusters, pushing throughput with large-batch serving and efficient resource utilization
  • Implement efficient low-level code (CUDA, Triton, custom kernels) and integrate it seamlessly into high-level frameworks
  • Optimize workloads for both throughput (batching, scheduling, quantization) and latency (caching, memory management, graph compilation)
  • Develop monitoring and debugging tools to guarantee reliability, determinism, and rapid diagnosis of regressions across both stacks

Qualifications

  • Deep experience in distributed systems, ML infrastructure, or high-performance serving (8+ years)
  • Production-grade expertise in Python, with strong background in systems languages (C++/Rust/Go)
  • Low-level performance mastery: CUDA, Triton, kernel optimization, quantization, memory and compute scheduling
  • Proven track record scaling inference workloads in both throughput-oriented cluster environments and latency-critical on-device deployments
  • System-level mindset with a history of tuning hardware–software interactions for maximum efficiency, throughput, and responsiveness

Skills

Required:Distributed systemsPythonC++/Rust/GoCUDATritonKernel optimizationQuantizationMemory and compute scheduling
Nice to have:On-device deploymentsGPU clusters
Last updated Sep 24, 2026. Interested? Apply on the company site.

About Genesis

A new future is at hand.

We are a new generation of robotics builders, united by a shared mission to push the boundaries of physical AI.

AIGENEGenesisfrontier-labsheadline-ai-europe-100-2026intelligencerobotics
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