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Research Engineer

DYNA Robotics· Research
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Redwood City, CAFull-timePosted 10mo ago

About the role

Dyna Robotics seeks a Research Engineer to own end-to-end training and inference infrastructure for embodied AI-powered robots, enabling scalable multi-cloud distributed training and low-latency real-time inference on hardware.

Responsibilities

  • Scale distributed training across a multi-cloud GPU fleet using sharding, activation checkpointing, and memory optimization (FSDP, ZeRO).
  • Build a research codebase and scheduling system (Kubernetes/SLURM) built for fast iteration, automatic retries, and painless failure recovery.
  • Design high-throughput pipelines for terabytes of multimodal robot data so dataloaders never starve the GPUs.
  • Ship low-latency inference for real-time robot control using quantization, distillation, and compilation (TensorRT, Triton).
  • Profile GPU utilization, I/O bottlenecks, and memory fragmentation to get the most out of every node.

Qualifications

  • 7+ years of engineering experience, including leading projects in HPC or ML infrastructure.
  • Know PyTorch and distributed training deeply (DeepSpeed, Accelerate, FSDP), including mixed precision and gradient accumulation.
  • Hands-on experience with cloud GPU environments (GCP/AWS) and Kubernetes.
  • Understand distributed systems at a low level: race conditions, memory management, NCCL and inter-node communication.
  • Own what you ship: you design, build, and operate systems end to end to unblock fast-moving research.

Skills

Required:Distributed trainingPyTorchDeepSpeed / Accelerate / FSDPKubernetes
Nice to have:SLURM
Last updated Oct 14, 2026. Interested? Apply on the company site.

About DYNA Robotics

Commercial-Grade Robots for Real-World Automation

DYNA: The first production-ready foundation model robot — built to reliably deploy in the wild.

DYNA-1automationcommercial robotsdual-arm robotsfactory automationphysical-ai-funding-landscapereal-world roboticsrestaurant automation
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