Yotta Labs Visa Sponsorship USA
Yotta Labs is a technology and software company that sponsors H-1B visas for skilled workers looking to build their careers in the U.S. For international candidates in the tech space, Yotta Labs represents a direct path to U.S. work authorization through one of the most in-demand visa categories.
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Get Access To All JobsLocation: Remote (Global)
Type: Full-time
Company: Yotta Labs
About Yotta Labs
Yotta Labs is pioneering the development of a Decentralized Operating System (DeOS) for AI workload orchestration at a planetary scale. Our mission is to democratize access to AI resources by aggregating geo-distributed GPUs, enabling high-performance computing for AI training and inference on a wide spectrum of hardware—from commodity to high-end GPUs. Our platform supports major large language models (LLMs) and offers customizable solutions for new models, facilitating elastic and efficient AI development.
Role Overview
We are seeking a GPU Cloud Platform Engineer to join our core infrastructure team and help build the next-generation AI compute cloud. In this role, you will design, deploy, and operate large-scale, multi-cluster GPU infrastructure across data centers and cloud environments. You will be responsible for ensuring high availability, performance, and efficiency of containerized AI workloads—ranging from LLMs to generative models—deployed in Kubernetes-based GPU clusters. If you're passionate about high-performance systems, distributed orchestration, and scaling real-world AI infrastructure, this role offers a unique opportunity to shape the backbone of our AI cloud platform.
Responsibilities
- Build and operate large-scale, high-performance GPU clusters; ensure stable operation of compute, network, and storage systems; monitor and troubleshoot online issues.
- Conduct performance testing and evaluation of multi-node GPU clusters using standard benchmarking tools to identify and resolve performance bottlenecks.
- Deploy and orchestrate large models (e.g., LLMs, video generation models) across multi-cluster environments using Kubernetes; implement elastic scaling and cross-cluster load balancing to ensure efficient service response under high concurrency for global users.
- Participate in the design, development, and iteration of GPU cluster scheduling and optimization systems. Define and lead Kubernetes multi-cluster configuration standards; Optimize scheduling strategies (e.g., node affinity, taints/tolerations) to improve GPU resource utilization.
- Build a unified multi-cluster management and monitoring system to support cross-region resource monitoring, traffic scheduling, and fault failover. Collect key metrics such as GPU memory usage, QPS, and response latency in real time; configure alert mechanisms.
- Coordinate with IDC providers for planning and deploying large-scale GPU clusters, networks, and storage infrastructure to support internal cloud platforms and external customer needs.
Qualifications
- Bachelor's degree or higher in Computer Science, Software Engineering, Electronic Engineering, or related fields; 3+ years of experience in system engineering or DevOps.
- 5+ years of experience in cloud-native development or AI engineering, with at least 2 years of hands-on experience in Kubernetes multi-cluster management and orchestration.
- Familiarity with the Kubernetes ecosystem; hands-on experience with tools such as kubectl, Helm, and expertise in multi-cluster deployment, upgrade, scaling, and disaster recovery.
- Proficient in Docker and containerization technologies; knowledge of image management and cross-cluster distribution.
- Experience with monitoring tools such as Prometheus and Grafana; Has practical experience in GPU fault monitoring and alerting.
- Hands-on experience with cloud platforms such as AWS, GCP, or Azure; understanding of cloud-native multi-cluster architecture.
- Experience with cluster management tools such as Ray, Slurm, KubeSphere, Rancher, Karmada is a plus.
- Familiarity with distributed file systems such as NFS, JuiceFS, CephFS, or Lustre; ability to diagnose and resolve performance bottlenecks.
- Understanding of high-performance communication protocols such as IB, RoCE, NVLink, and PCIe.
- Strong communication skills, self-motivation, and team collaboration.
Preferred Experience
- Experience in developing and operating MaaS platforms or large-scale model inference clusters. Proven track record of leading multi-cluster system development or performance optimization projects.
- Proficiency in CUDA programming and the NCCL communication library; understanding of high-performance GPUs like H100.
- Ability to develop standardized inference APIs (RESTful/gRPC) and automation tools using Golang or Python.
- Hands-on experience with optimization techniques such as model quantization, static compilation, and multi-GPU parallelism; capable of profiling inference processes in multi-cluster setups and identifying bottlenecks like memory fragmentation and low compute efficiency.
- Active engagement with open-source communities such as Hugging Face and GitHub; deep understanding of the design principles of inference frameworks like Triton, vLLM, and SGLang; ability to perform secondary development and optimization based on open-source projects and quickly translate cutting-edge techniques into production-ready multi-cluster solutions.
Why Join Yotta Labs?
- Be part of a visionary team aiming to redefine AI infrastructure.
- Work on cutting-edge technologies that bridge AI and decentralized computing.
- Collaborate with experts from leading institutions and tech companies.
- Enjoy a flexible, remote work environment that values innovation and autonomy.
How to Apply
Interested candidates should apply directly or send their resume and a brief cover letter to careers@yottalabs.ai. Please include links to any relevant projects or contributions.
Location: Remote (Global)
Type: Full-time
Company: Yotta Labs
About Yotta Labs
Yotta Labs is pioneering the development of a Decentralized Operating System (DeOS) for AI workload orchestration at a planetary scale. Our mission is to democratize access to AI resources by aggregating geo-distributed GPUs, enabling high-performance computing for AI training and inference on a wide spectrum of hardware—from commodity to high-end GPUs. Our platform supports major large language models (LLMs) and offers customizable solutions for new models, facilitating elastic and efficient AI development.
Role Overview
We are seeking a GPU Cloud Platform Engineer to join our core infrastructure team and help build the next-generation AI compute cloud. In this role, you will design, deploy, and operate large-scale, multi-cluster GPU infrastructure across data centers and cloud environments. You will be responsible for ensuring high availability, performance, and efficiency of containerized AI workloads—ranging from LLMs to generative models—deployed in Kubernetes-based GPU clusters. If you're passionate about high-performance systems, distributed orchestration, and scaling real-world AI infrastructure, this role offers a unique opportunity to shape the backbone of our AI cloud platform.
Responsibilities
- Build and operate large-scale, high-performance GPU clusters; ensure stable operation of compute, network, and storage systems; monitor and troubleshoot online issues.
- Conduct performance testing and evaluation of multi-node GPU clusters using standard benchmarking tools to identify and resolve performance bottlenecks.
- Deploy and orchestrate large models (e.g., LLMs, video generation models) across multi-cluster environments using Kubernetes; implement elastic scaling and cross-cluster load balancing to ensure efficient service response under high concurrency for global users.
- Participate in the design, development, and iteration of GPU cluster scheduling and optimization systems. Define and lead Kubernetes multi-cluster configuration standards; Optimize scheduling strategies (e.g., node affinity, taints/tolerations) to improve GPU resource utilization.
- Build a unified multi-cluster management and monitoring system to support cross-region resource monitoring, traffic scheduling, and fault failover. Collect key metrics such as GPU memory usage, QPS, and response latency in real time; configure alert mechanisms.
- Coordinate with IDC providers for planning and deploying large-scale GPU clusters, networks, and storage infrastructure to support internal cloud platforms and external customer needs.
Qualifications
- Bachelor's degree or higher in Computer Science, Software Engineering, Electronic Engineering, or related fields; 3+ years of experience in system engineering or DevOps.
- 5+ years of experience in cloud-native development or AI engineering, with at least 2 years of hands-on experience in Kubernetes multi-cluster management and orchestration.
- Familiarity with the Kubernetes ecosystem; hands-on experience with tools such as kubectl, Helm, and expertise in multi-cluster deployment, upgrade, scaling, and disaster recovery.
- Proficient in Docker and containerization technologies; knowledge of image management and cross-cluster distribution.
- Experience with monitoring tools such as Prometheus and Grafana; Has practical experience in GPU fault monitoring and alerting.
- Hands-on experience with cloud platforms such as AWS, GCP, or Azure; understanding of cloud-native multi-cluster architecture.
- Experience with cluster management tools such as Ray, Slurm, KubeSphere, Rancher, Karmada is a plus.
- Familiarity with distributed file systems such as NFS, JuiceFS, CephFS, or Lustre; ability to diagnose and resolve performance bottlenecks.
- Understanding of high-performance communication protocols such as IB, RoCE, NVLink, and PCIe.
- Strong communication skills, self-motivation, and team collaboration.
Preferred Experience
- Experience in developing and operating MaaS platforms or large-scale model inference clusters. Proven track record of leading multi-cluster system development or performance optimization projects.
- Proficiency in CUDA programming and the NCCL communication library; understanding of high-performance GPUs like H100.
- Ability to develop standardized inference APIs (RESTful/gRPC) and automation tools using Golang or Python.
- Hands-on experience with optimization techniques such as model quantization, static compilation, and multi-GPU parallelism; capable of profiling inference processes in multi-cluster setups and identifying bottlenecks like memory fragmentation and low compute efficiency.
- Active engagement with open-source communities such as Hugging Face and GitHub; deep understanding of the design principles of inference frameworks like Triton, vLLM, and SGLang; ability to perform secondary development and optimization based on open-source projects and quickly translate cutting-edge techniques into production-ready multi-cluster solutions.
Why Join Yotta Labs?
- Be part of a visionary team aiming to redefine AI infrastructure.
- Work on cutting-edge technologies that bridge AI and decentralized computing.
- Collaborate with experts from leading institutions and tech companies.
- Enjoy a flexible, remote work environment that values innovation and autonomy.
How to Apply
Interested candidates should apply directly or send their resume and a brief cover letter to careers@yottalabs.ai. Please include links to any relevant projects or contributions.
Job Roles at Yotta Labs Companies
How to Get Visa Sponsorship in Yotta Labs Visa Sponsorship USA
Target roles that align with H-1B specialty occupation requirements
Yotta Labs sponsors H-1B visas, which require a direct connection between your degree and the job. Focus your application on technical and software roles where your academic background clearly supports the specialty occupation standard.
Research Yotta Labs' product and technology stack before applying
As a technology and software company, Yotta Labs values candidates who understand their domain. Tailoring your resume and cover letter to their specific tech focus signals genuine interest and strengthens your case for sponsorship consideration.
Apply early in the calendar year with the H-1B lottery in mind
H-1B petitions are subject to an annual lottery with an April filing window. Targeting Yotta Labs roles in the first quarter gives your application time to move through internal review before the registration deadline.
Be transparent about your visa situation from the first conversation
Technology companies like Yotta Labs are familiar with the H-1B process. Raising your sponsorship needs early avoids wasted time and signals the kind of directness that resonates well with smaller, fast-moving tech employers.
Use Migrate Mate to find verified sponsoring employers in the tech space
Not every tech company sponsors visas consistently. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history, helping you focus your energy on companies like Yotta Labs that have an active sponsorship track record.
Highlight cross-functional impact, not just technical skills
At a technology and software company, engineers and technical specialists who demonstrate business impact alongside their expertise stand out. Framing your work in terms of outcomes strengthens your profile when sponsorship decisions involve multiple stakeholders.
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Get Access To All JobsFrequently Asked Questions
Does Yotta Labs sponsor H-1B visas?
Yes, Yotta Labs sponsors H-1B visas for qualified candidates in the technology and software space. The H-1B is designed for specialty occupation roles that require at least a bachelor's degree in a relevant field. If you're targeting a technical role at Yotta Labs, confirming the position qualifies as a specialty occupation is the first step before beginning the application process.
What types of roles at Yotta Labs are most likely to receive visa sponsorship?
As a technology and software company, Yotta Labs' sponsorship activity is concentrated in technical roles such as software engineering, product development, and data-related positions. These are the job categories most commonly associated with H-1B sponsorship across the industry, as they typically meet the specialty occupation requirements USCIS looks for when reviewing petitions.
How do I find open jobs at Yotta Labs that offer visa sponsorship?
Migrate Mate is the most efficient way to find roles at companies like Yotta Labs with a verified H-1B sponsorship history. Searching directly through the company's careers page is also worth doing, but pairing that with Migrate Mate's sponsorship filter ensures you're only investing time in employers who have genuinely sponsored visas before.
How do I approach the application process at Yotta Labs as an H-1B candidate?
Start by identifying roles where your degree directly supports the specialty occupation requirement. Reach out early, disclose your visa needs clearly, and be prepared to discuss your timeline relative to the H-1B lottery window. Smaller technology companies often appreciate candidates who understand the process and come prepared, rather than leaving sponsorship logistics to be figured out later.
What should I know about Yotta Labs' sponsorship track record before applying?
Yotta Labs has an established history of sponsoring H-1B visas in the technology and software sector. While their sponsorship volume is more selective than large enterprise tech employers, that can work in your favor as a candidate, smaller teams often make sponsorship decisions faster and with more direct input from hiring managers rather than through lengthy HR approval chains.
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