Yotta Labs is at the forefront of building the next generation multi-silicon AI cloud and runtime platform. We enable training and inference across NVIDIA GPUs, AMD GPUs, and AWS Trainium/Inferentia, helping AI companies achieve the best performance and economics across heterogeneous hardware
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Building the next generation multi-silicon AI cloud and runtime platform.
Full company description
Yotta Labs is at the forefront of building the next generation multi-silicon AI cloud and runtime platform. We enable training and inference across NVIDIA GPUs, AMD GPUs, and AWS Trainium/Inferentia, helping AI companies achieve the best performance and economics across heterogeneous hardware
LinkedIn followers
741
People associated on LinkedIn
7
Reported office locations
Seattle, US
Business categories
GPU
Cloud Computing
Artificial Intelligence (AI)
Other recorded names
Yotta Labs
Profile identifies a recruitment agency
No
Reported total investment
0
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Industry
Technology, Information and Internet
Size
2-10 employees
Headquarters
Seattle
Organization type
Public Company
Year founded
2024
Yotta Labs has 3 open jobs in Canada as of November 6, 2026.
Yotta Labs needs candidates currently enrolled in a BS, MS or PhD program in computer science or computer engineering. They should have solid Python skills, some C++ knowledge, and experience writing GPU kernels from coursework or personal projects.
Candidates need strong Python and C++ skills, deep GPU architecture knowledge and experience with CUDA, Triton, ROCm or AWS Neuron. A background in computer science or engineering is preferred, along with the ability to work collaboratively in a remote team.
5+ YOECandidates need a bachelor's degree or higher in a technical field, 3+ years in systems engineering or DevOps, and 5+ years in cloud-native or AI engineering. Hands-on Kubernetes multi-cluster experience, Docker, Prometheus and Grafana are required.