--- title: 'Sales Manager – GPU Compute & AI Model APIs at Yotta Labs' canonical: 'https://feeny.ai/job/sales-manager-gpu-compute-ai-model-apis-yotta-labs-united-states-1e6jc75ddqea' type: 'job' last_seen: '2026-09-09' --- # Sales Manager – GPU Compute & AI Model APIs at Yotta Labs - **Company:** Yotta Labs - **Location:** United States - **Employment:** full-time - **Work type:** remote - **Posted:** 2026-03-30 - **Last confirmed live:** 2026-09-09 - **Apply:** https://jobs.ashbyhq.com/yotta/30e75db2-14e2-433c-bdf6-cec7334615f0 ## Job description Location: Remote (North America) Type: Full-time Company: Yotta Labs Apply: careers@yottalabs.ai 🧠 About Yotta Labs Yotta Labs is building the next generation multi-silicon AI cloud and runtime platform to power the world’s most demanding AI workloads. We enable training and inference across NVIDIA GPUs, AMD GPUs, and AWS Trainium, helping AI companies achieve the best performance and economics across heterogeneous hardware. Our mission is to provide high-performance AI computing and Model API services, enabling AI companies, research labs, and enterprises to train, deploy and integrate cutting-edge models at scale. 🛠️ Role Overview We are hiring a Sales Manager – GPU Compute & AI Model APIs to drive revenue growth and build our sales function from the ground up. You will own two core revenue lines: GPU compute sales (on-demand and reserved GPU capacity for AI training and inference) and Model API sales (managed API access to leading LLMs and custom models). This is a hands-on role—you’ll be directly engaging customers, closing deals, and growing accounts while helping shape our go-to-market strategy. As a core member of a lean startup team, you’ll combine frontline sales execution with strategic input on product and pricing. Ideal for someone who loves building and isn’t afraid to roll up their sleeves. 🎯 Responsibilities - Own the full sales lifecycle for both GPU compute and Model API products—from prospecting and qualifying leads to closing deals and expanding long-term partnerships. - Drive GPU compute revenue by identifying organizations with large-scale training, fine-tuning, and inference workloads, positioning Yotta Labs as their preferred infrastructure provider. - Grow Model API adoption by engaging AI application developers, SaaS companies, and enterprises looking for reliable, scalable, and cost-effective API access to leading LLMs. - Develop and execute outbound sales strategies targeting high-value accounts across AI startups, research labs, and enterprise customers scaling AI workloads. - Work closely with marketing to create compelling sales collateral, case studies, and campaigns that highlight our GPU compute and Model API value propositions. - Navigate complex technical and commercial conversations, collaborating with engineering and product teams to tailor solutions to customer requirements. - Consistently meet or exceed revenue and ARR targets, contributing to the growth of a repeatable and scalable sales motion. - Represent Yotta Labs at industry conferences, AI/ML meetups, and customer meetings to grow our presence in the AI infrastructure ecosystem. ✅ Qualifications - 3+ years of experience in sales or business development in cloud infrastructure, GPU compute, AI/ML platforms, or a related technical domain. - Strong understanding of the GPU cloud market, AI/ML workflows, model training/inference pipelines, and the compute requirements of modern AI applications. - Proven track record of closing complex B2B deals and growing accounts in high-growth or technical markets. - Familiarity with Model API/LLM-as-a-Service offerings and the ability to articulate technical differentiation to both developers and business stakeholders. - Deep network in the AI and/or cloud infrastructure ecosystem with an ability to initiate and nurture executive-level relationships. - Exceptional communication and negotiation skills; comfort working directly with technical and business stakeholders. - Highly self-motivated, with strong execution skills and the ability to operate autonomously in a startup environment. 🌟 Preferred Experience - Previous experience at a GPU cloud provider (e.g., CoreWeave, Lambda, Together AI), AI infrastructure startup, or cloud hyperscaler. - Hands-on experience selling GPU compute capacity, reserved instances, or cloud AI/ML services. - Experience selling API-based AI products or working with teams that build on LLM APIs (e.g., OpenAI, Anthropic, or similar). - Experience working with AI research teams, MLOps engineering groups, or AI application developers. - Familiarity with container orchestration (Kubernetes), AI developer tooling, and modern ML infrastructure stacks. - Background in computer science, engineering, or a related technical discipline. 🌐 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. ## About Yotta Labs ## Company Overview - **One-liner**: Yotta Labs is building an interoperable AI infrastructure operating system that orchestrates AI workloads across multi-cloud and multi-silicon environments, turning fragmented GPU capacity into a unified execution fabric. - **Entity Type**: Private (Seed Stage) - **Headquarters**: Seattle, Washington, USA - **Founded**: 2024 - **Founders**: Da Li (CEO) and a team of experts in AI and High-Performance Computing (HPC) ## Core Business - **Primary Industry**: AI Infrastructure / Cloud Computing / Decentralized Compute - **Target Customers**: AI-native and enterprise teams deploying production AI systems (training, fine-tuning, and inference) - **Mission/Purpose**: To make AI compute interoperable, elastic, and efficient by default, enabling workloads to move fluidly across clouds, regions, and silicon generations without vendor lock-in. ## Products & Services - **Interoperable AI OS (Yotta Platform)**: A unified execution and orchestration control plane that abstracts differences across cloud providers and GPU architectures (NVIDIA, AMD, emerging accelerators). Enables multi-cloud, multi-silicon AI workload deployment and scheduling from a single pane of glass. - **Compute Products (under the Yotta OS)**: - **Pods**: On-demand GPU environments (VMs) for training and inference. - **Serverless**: Automatically scaling inference and batch processing across regions. - **Launch Specs**: Pre-configured, one-click deployment specs for instant setup. - **Open Source Tools**: High-performance GPU kernels for AMD inference (GitHub) and optimized neural network memory management. - **Decentralized OS (DeOS)**: A protocol and network for orchestrating workloads across geo-distributed GPUs globally, aiming for "Yottascale" (1 million times exascale) processing. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed. - **Key Metrics**: - **Total Funding**: $300,000 in Grant funding; a Seed Round (led by Big Brain Holdings, Eden Block) raised on October 30, 2025 (with 6 investors, amount undisclosed). - **Scale**: Reports over 1 million Pods deployed and 50,000+ developers on platform. Operates in 20+ global regions. - **Notable Investors/Partners**: Big Brain Holdings, Eden Block; National Science Foundation (NSF) grant recipient; Advisory board includes Jack Dongarra (ACM A.M. Turing Award winner). - **Growth Signals**: Headcount has grown +166.7% (from 2 to ~6 employees) since founding in 2024. Active job postings have grown +1500% yearly, with 16 open roles. Recent high-profile media coverage in VentureBeat ("Interoperable AI OS for multi-cloud compute liquidity"). ## Competitive Advantages - **Multi-Silicon & Multi-Cloud Abstraction**: Unlike single-cloud solutions, Yotta is architected to treat heterogeneous infrastructure (NVIDIA, AMD, and emerging accelerators) as a first-class feature, not a workaround. - **Hardware-Aware Scheduling**: Dynamically routes workloads to the most cost-effective and available hardware across different regions and power grids, enabling lower costs and higher utilization. - **Production-First Design**: Built for reliability, observability, and enterprise compliance (SOC 2), making it suitable for production AI teams rather than experimental demos. - **Elastic & Interoperable Compute**: The ability to move workloads across clouds and regions without rewriting infrastructure logic solves the "lock-in" problem for large-scale AI. ## Strategic Focus - **Building the Interoperable AI OS**: The current priority is establishing Yotta as the default operating system for multi-cloud, multi-silicon AI execution. - **Decentralized Orchestration**: Expanding the DeOS protocol to unlock compute liquidity from smaller, stranded, or underutilized GPU resources globally. - **Scaling the Team**: Aggressively hiring across Engineering (GPU Cloud Platform, Research Engineers), Developer Relations (AI Developer Advocates), and GTM roles to build out the product and user base. ## Why Work Here - **Culture & Mission**: Working on a foundational problem in AI infrastructure (fragmentation and vendor lock-in) with a high-impact, research-driven team. - **Team & Advisory**: Backed by a team with deep expertise in distributed systems, HPC, and national labs, advised by Turing Award winner Jack Dongarra. - **Work Location**: Remote-friendly with an HQ in Seattle, Washington, USA. Several open roles list "Remote" as an option. - **Growth Stage**: Early-stage startup (~6 employees) with massive headcount growth plans (+1500% YoY in job postings), offering significant ownership and impact for early hires. - **Technical Depth**: Work involves kernel optimization, distributed execution, scheduling, and reliability at scale across cutting-edge hardware (H100, B200, AMD GPUs). ## Sources 1. [yottalabs.ai](https://www.yottalabs.ai/) 2. [LinkedIn](https://www.linkedin.com/company/yotta-labs) 3. [VentureBeat](https://venturebeat.com/business/interoperable-ai-os-for-multi-cloud-compute-liquidity-inside-yotta-labs) 4. [docs.yottalabs.ai](https://docs.yottalabs.ai/) 5. [Built In](https://builtin.com/company/yotta-labs) ## Other roles at Yotta Labs - [Research Engineer Intern - AI Systems](https://feeny.ai/job/research-engineer-intern-ai-systems-yotta-labs-united-states-277v5vq84m8f) — United States - [Research Engineer - AI Systems](https://feeny.ai/job/research-engineer-ai-systems-yotta-labs-united-states-rw7ey5zxc2ps) — United States - [GPU Cloud Platform Engineer](https://feeny.ai/job/gpu-cloud-platform-engineer-yotta-labs-united-states-fevfkq8ppjmw) — United States