Yotta Labs

Building the GPU Cloud for efficient ML with heterogeneous hardware and cross-cloud orchestration

1-10 employees
Artificial Intelligence (AI)
Private Company

Remote Work Available

This company offers remote work opportunities.

Open Positions4

United StatesHong KongCanadaSingaporeInternshipAI InfrastructurePosted
  • Implement and optimize compute kernels for Attention, GEMM, MoE, and quantization on NVIDIA, AMD, or AWS Trainium.
  • Build custom operators using CUDA, Triton, ROCm/HIP, or the Neuron SDK with PyTorch/XLA.
  • Profile and improve inference performance in vLLM, SGLang, and custom runtimes including kernel fusion, scheduling, KV-cache, and memory optimizations.
  • Build benchmarks, identify performance regressions, and convert profiler traces into performance improvements.
  • Ship code upstream to open-source AI infrastructure projects, including tests and documentation.
PythonFGPA ArchitecturePyTorch+1 more
Showing 1 of 4 positions

About Yotta Labs

Yotta Labs is building the GPU Cloud for efficient machine learning, pioneering a Decentralized Operating System (DeOS) to orchestrate AI workloads across diverse hardware at a planetary scale. You can access on-demand GPU instances and Model APIs, enabling AI companies, research labs, and enterprises to train and deploy cutting-edge models. Their platform aggregates geo-distributed GPUs, offering elastic and cost-effective access to AI compute. They unify fragmented GPU capacity into a single execution fabric, making high-performance computing accessible for AI training and inference. You can deploy GPU pods in under 3 seconds.

How We Work

You will find a flexible, remote work environment that values innovation and autonomy. Your team members are encouraged to collaborate and contribute to open-source projects. You will work within a small, focused team, directly impacting strategic decisions. This environment supports strong problem-solving skills and independent contribution.

Engineering at Yotta Labs

You will build the next-generation AI infrastructure, developing a Decentralized Operating System (DeOS) for AI workload orchestration across multi-cloud and multi-silicon environments. Engineers optimize AI workloads across a heterogeneous network of GPUs. Your work will involve cutting-edge technologies that bridge AI and decentralized computing. You will contribute to high-performance computing for AI training and inference on a wide spectrum of hardware. This means tackling challenges in distributed systems, cloud computing, and blockchain technologies.

Why Join Us

  • Be part of a visionary team redefining AI infrastructure.
  • Work on cutting-edge technologies bridging AI and decentralized computing.
  • Collaborate with experts from leading institutions and tech companies.
  • Enjoy a flexible, remote work environment valuing innovation and autonomy.
  • Directly impact the scalability and performance of AI applications.

Benefits & Perks

  • Flexible, remote work environment
  • Autonomy in your role

Tech Stack

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