Sales Development Representative

NVIDIA Cloud Partners scale across Europe - sovereign, open and built for safe AI agents. Growing ecosystem of AI clouds across Europe, Nordics, Africa and Central Asia build full-stack NVIDIA DSX Vera Rubin AI factories as AI-native companies drive demand for sovereign compute, training, inference and post-training services. Demand from AI-natives is pulling the European AI cloud ecosystem forward faster than ever. Developers need compute closer to their data, open models they can customize and serve at scale, and full-stack infrastructure that is secure by design. NVIDIA Cloud Partners across Europe, the Nordics, Africa, and Central Asia are expanding regional compute capacity for model training and inference, helping developers build agentic and physical AI applications, and establishing boundaries around what agents can access and do. Together, they're turning Europe's energy, data, research and industrial expertise into productive intelligence - supporting new models, applications, organizations and jobs while giving people more control over where and how they develop and deploy AI. Sovereign: AI clouds building European AI infrastructure. Europe is home to world-class research, engineering talent, industrial expertise, data, the next generation of models and applications that requires large-scale computing close to where that knowledge resides. Regional AI clouds provide the infrastructure foundation on which model builders, enterprises and entire industries can grow. As AI factories scale, power becomes a constraint which makes it critical for every watt to produce more intelligence. Nscale is using the NVIDIA DSX Platform to coordinate power allocation with workload requirements. In tests using NVIDIA GB300 NVL72 systems, Nscale demonstrated that NVIDIA DSX MaxLPS enabled 37% more GPUs and nearly 50% higher aggregate inference throughput within the same provisioned power budget. Nscale also plans to deploy NVIDIA Vera Rubin infrastructure for frontier-model training and production workloads to support leading model and application builders using its full-stack, vertically integrated platform with expansion across five European markets. Crusoe is developing Spark, its liquid-cooled modular AI factories designed for the NVIDIA Vera Rubin platform, to bring Crusoe Cloud capacity closer to users for low-latency AI inference. Crusoe Cloud serves leading model and application builders across EMEA, including Base44, Gradium, LTX and Wonderful. Aleria, Cassava Technologies, Firebird, G42, Radiant, SWI Compute and Vultr are also developing and expanding NVIDIA-powered AI infrastructure across Europe, the Nordics, Africa and Central Asia. Regional capacity from AI clouds combines the full-stack NVIDIA DSX AI Factory platform, including NVIDIA Vera Rubin, NVIDIA BlueField and NVIDIA Spectrum-X Ethernet networking, giving customers greater choice and control over where workloads and data reside while advancing sovereign computing services and economic growth. Open: models and libraries, from training to inference. Across the ecosystem, AI clouds are expanding NVIDIA-powered infrastructure and services for developers to build applications with open models and libraries. This new capacity supports model training, fine-tuning for specialized tasks and inference at scale, including applications deployed at the edge. For production inference, Nebius has adopted NVIDIA Groq 3 LPX, using Spectrum-X Ethernet networking to integrate it with Vera Rubin NVL72 on Nebius Token Factory. The combination will bring faster token generation to latency-sensitive applications and agentic systems through the platform's managed serverless and dedicated endpoints and familiar application programming interfaces. For robotics and physical AI, Nebius offers a purpose-built AI cloud solution that includes its full-stack Physical AI Workbench. Robotics companies including Rhoda AI, RoboForce and Sereact are building on the platform. The company also launched three NVIDIA retail agent blueprints - covering inventory, store operations, and fine-tuning - - into early access on Nebius infrastructure. Nebius is expanding its cloud services widely across the continent with its Physical AI Living Lab, and in Germany as a computer supplier for the Next Frontier Challenge of SPRIND, the Federal Agency for Breakthrough Innovation. Baseten has developed a specialized model for code-review routing with Nemotron 3.5 Lightning used by CodeRabbit. Through supervised fine-tuning and reinforcement learning, CodeRabbit improved routing agreement from 75.8% to 80.7% while reducing estimated inference costs by 50% for the evaluated workload. The results demonstrate how AI developers can customize NVIDIA open models for specialized tasks while improving accuracy and inference efficiency. Fireworks and Era4 are partnering to bring open models to enterprises across the U.K. and Europe. The collaboration combines Fireworks' model training and inference platform with direct liquid-cooled capacity powered by NVIDIA Blackwell Ultra GPUs at Era4's Chesterfield facility, supporting plans for enterprise AI solutions in financial services, insurance and life sciences. Mistral is expanding its NVIDIA accelerated computing infrastructure to support model training, customization and inference. The expansion includes NVIDIA Vera Rubin infrastructure planned for delivery in 2027. Trained on 3,800 NVIDIA Grace Blackwell GPUs in Mistral-operated European data centers, Mistral Large 4 is the company's latest frontier multimodal model, advancing capabilities across coding, agentic workflows and multimodal understanding. Verda plans to deploy NVIDIA Vera Rubin, continuing to promote open weight models with NVIDIA Nemotron and NVIDIA Cosmos already in production, and using the NVIDIA Dynamo open source framework for inference optimization. Safe: secure boundaries for AI agents, from silicon to software. As developers connect models to tools and business systems, they also need controls over what agents can access and do. Announced at GTC Berlin, the NVIDIA OpenShell Reference Architecture with support from AI cloud ecosystem partners. Built on the foundation of NVIDIA OpenShell secure runtime software, the architecture is designed to give organizations full-stack control to deploy AI agents with clear boundaries around what agents can access and do. NVIDIA Vera Rubin NVL72 for model inference, NVIDIA Vera CPUs with OpenShell for agent harnesses and tool use, and NVIDIA BlueField-4 DPUs running NVIDIA Sentry for in-silicon enforcement. Each play a distinct role in delivering that control, working together so agents can achieve what they're meant to do without moving beyond the boundaries people set for them. Partners including Aleria, Baseten, Cassava, CoreWeave, Crusoe, DigitalOcean, Firebird, Fireworks, Firmus, G42, GMI Cloud, IREN, Lambda, Lightning AI, Nebius, Nscale, Radiant Verda and Vultr are supporting the OpenShell Reference Architecture to enable secure agentic deployments for their customers. Together, European AI clouds are connecting regional infrastructure investment with the work of building and deploying AI. Expanded capacity gives builders more places to run workloads. Model and inference services help them put that capacity to use. Agent controls address what applications are allowed to do as they move into production. Explore NVIDIA Cloud Partners for infrastructure and services, and the OpenShell Reference Architecture for agent deployment controls.

Fireworks AI seeks new funding, targeting a $30-40 billion valuation. Investor appetite for the infrastructure underpinning artificial intelligence continues to surge, as Fireworks AI seeks to raise new capital at a valuation between $30 billion and $40 billion, according to people familiar with the matter. This potential jump comes only months after the company's last fundraising round in July, which valued the startup at $17.5 billion. Founded in 2022 by veterans from Meta and Google's AI divisions, the San Francisco-based company has quickly established itself as a key player in the competitive world of AI infrastructure. Fireworks AI develops and rents out the computing systems and software tools that businesses use to run, fine-tune, and deploy both open-weight and custom AI models. The company distinguishes itself by focusing on what it calls "specialized intelligence," tailoring AI models to clients' proprietary data, workflows, and specific use cases, rather than building a consumer-facing chatbot to rival ChatGPT. Demand for AI infrastructure solutions has soared as companies seek to harness generative AI technologies. In July, Fireworks AI revealed that it had surpassed $1 billion in annualized revenue, serving more than 40 trillion tokens per day, with 95 percent of activity attributed to customer-specific models. The firm's clientele ranges from startups fine-tuning open models to larger enterprises integrating AI directly into their operations. Fireworks has become a magnet for top-tier investors. Its $1.5 billion Series D round this July was led by Atreides Management, Index Ventures, and TCV and included participation from Nvidia, Lightspeed Venture Partners, Bessemer Venture Partners, and Menlo Ventures. The prior Series C, in late 2025, brought in $250 million at a $4 billion valuation, co-led by Lightspeed, Index, and Evantic. The current funding talks come as Fireworks AI has been navigating the aftermath of a security incident. Earlier this month, the company reported discovering unauthorized use of internal credentials that allowed an intruder to access data from some customer accounts. Chief executive Lin Qiao, who previously led the PyTorch team at Meta, wrote on X that the company is committed to transparency and to turning the episode into "the most formidable security response in AI Infra." Fireworks declined to comment further on both the security matter and the fundraising process. Fireworks operates in a fiercely competitive sector, facing challenges from other model-infrastructure startups such as Together AI, Baseten, and Replicate, as well as from tech giants like Amazon Web Services, Google Cloud, Microsoft Azure, and Oracle. The company's plans for a new funding round, first reported last month by The Information, have not been finalized, and valuation targets may still change as discussions continue. Still, the staggering jump in valuation highlights the ongoing excitement surrounding AI infrastructure providers, even as operational and security challenges persist. Investors are betting that companies like Fireworks AI will remain critical to the booming adoption of artificial intelligence across industries. Technology

Fireworks AI is in talks to double its valuation to 40 billion dollars. Fireworks AI processes over 40 trillion tokens daily and crossed $1 billion in annualized revenue, up fivefold in a year, as Nvidia, Index Ventures and TCV back its rapid valuation climb. An inference startup most people outside AI circles have never heard of is closing in on a valuation that would put it ahead of companies that actually build the models. Fireworks AI is a Redwood City startup. It helps companies run AI models cheaply and fast, and it's now in early talks to raise new funding at a valuation between $30 billion and $40 billion, Business Insider reported on October 20. That's roughly double what the company was worth just three months ago. Back in July it closed a $1.505 billion Series D at a $17.5 billion valuation, led by Atreides Management, Index Ventures and TCV, with Nvidia joining as a follow-on investor. Founder Lin Qiao isn't new to this stack. She left Meta in 2022, where she led more than 300 engineers building and scaling PyTorch, the open-source framework that still trains and runs a large share of the world's AI models. She started Fireworks in Redwood City a month before ChatGPT launched, betting that whoever controlled the plumbing between a trained model and a paying customer would matter as much as whoever trained the model in the first place. That bet is paying off. Fireworks now processes more than 40 trillion tokens a day, up from roughly 15 trillion a year ago, and has crossed $1 billion in annualized revenue, about five times what it was generating last year. More than 95% of that traffic comes from models customers have fine-tuned on their own proprietary data, not off-the-shelf open weights. That's the part of the business Fireworks actually sells: leased GPU capacity plus the tooling to fine-tune and serve a model in production - not a frontier model of its own. Baseten closed a $1.5 billion Series F in June at a $13 billion valuation, barely five months after a $300 million round valued it at $5 billion. Together AI, another rival chasing the same enterprise inference workloads, closed an $800 million round at an $8.3 billion valuation after crossing $1 billion in annualized revenue of its own. The pattern across all three is the same: valuations are stepping up two, three, sometimes four times in a matter of months, far faster than revenue is actually growing underneath them. Fireworks AI closed a $1.505 billion Series D at a $17.5 billion valuation, nine months after a $4 billion Series C. The inference startup founded by ex-Meta PyTorch lead Lin Qiao has crossed $1 billion in annualized revenue, a fivefold jump year-over-year, and now processes 40 trillion tokens per day for customers including Cursor, Uber, and... - fireworks AI series D funding valuation - enterprise AI cheaper alternatives frontier models Here's the thing worth sitting with. Fireworks, Baseten and Together don't train frontier models, and they don't have the kind of proprietary data or model weights that create a durable moat. What they sell, fast and cheap model-serving, is increasingly commoditized, and the hyperscalers (AWS, Google Cloud, Microsoft Azure) all offer some version of it too. A customer who switches from Fireworks to Baseten loses very little. That's not a reason to assume these companies collapse. It's a reason their valuations should track revenue multiples closer to infrastructure resellers than to AI labs, and right now they aren't. Citadel's Ken Griffin has been the most prominent voice naming the mismatch directly. Speaking at the Future of Global Markets conference, Griffin said the AI boom's real payoff could take decades rather than years. The dream "could be 20 years... it can be 30 years" before the technology's value gets properly sorted between winners and losers, he warned, much like the dot-com crash separated Amazon from Pets.com. He wasn't talking about Fireworks specifically. But a 230% valuation jump in three months for a company that leases someone else's GPUs is exactly the kind of math his warning describes. None of this means the money is wrong to chase inference. Every major AI lab needs somewhere to actually run the models it trains, and that demand is real and growing. Nvidia followed its own Series D money into Fireworks as a strategic investor, rather than just selling it chips. That says the chipmaker sees the inference layer as a long-term fixture, not a bubble play it wants to avoid. But a strategic investor backing a company for supply-chain reasons is a different signal than a pure financial investor paying 40 billion dollars for a business that reported roughly 1 billion in revenue months earlier. Fireworks declined to comment on the specific terms of the talks, and Business Insider's report noted the round has not been finalized. If it closes anywhere near that range, Fireworks will be worth more than most publicly traded enterprise software companies, with a fraction of the public scrutiny. The rest of the inference sector will have a new ceiling to measure itself against. Join the discussion. No replies yet. Start the discussion. Janet Harrison has over 16 years experience in the financial services industry giving her a vast understanding of how news affects the financial markets, and an early adopter of blockchain technology and digital currencies. Janet is an active holder and trader spending the majority of her time analyzing blockchain projects, reports and watching new and upcoming projects and other initiatives in the industry. She has a Masters Degree in Economics with previous roles counting Investment Banking.