Runpod
AI Developer Cloud
The requested Runpod page could not be found. Return to Runpod to explore GPU cloud, serverless inference, and AI infrastructure resources.
Runpodは採用中ですか?
はい。2026年10月9日時点で、Metaintro にはRunpodの募集中のポジションが30 件あります。 過去30日間に9 件が掲載されました。
募集中のポジション
新しい順。求人に記載がある場合は給与を表示します。
- Director, Securityセキュリティリモート · $125K – $220K/yr—リモート$125K – $220K/yr昨日
- Affiliate & Creator Marketing Leadマーケティングリモート · $115K – $180K/yr—リモート$115K – $180K/yr3日前
- Senior Video Producerメディア制作リモート · $130K – $185K/yr—リモート$130K – $185K/yr4日前
- Cloud Infrastructure Security Engineer (Systems/Kernel)セキュリティリモート · $152K – $175K/yr—リモート$152K – $175K/yr4日前
- Senior ML Systems Engineer, Inference開発者リモート · $150K – $220K/yr—リモート$150K – $220K/yr8日前
- Account Manager (Strategic)営業リモート · $160K – $280K/yr—リモート$160K – $280K/yr15日前
- HPC Storage Engineer - West CoastDevOpsリモート · $150K – $220K/yr—リモート$150K – $220K/yr15日前
- Forward Deployed Engineer APACテクノロジー全般Apac · リモート · $100K – $160K/yrApacリモート$100K – $160K/yr16日前
採用パターン
Runpod が募集をどれだけのペースで増やしているか、そして勤務形態の内訳。
月別の新規募集その月に初めて掲載された求人
顧客
Runpod が顧客として挙げている 15 社すべて。
採用中の顧客1
- Coframe募集中 38 件

導入事例14
- OOpen Source Films
- BBottoDAO
- FFaceless.video
- NNodalview
- RRendair
- KKRNL
- IInstaHeadshots
- TTOOL
- SScatter Lab
- SSegmind
- GGendo
- GGlam Labs
- CCivitai
- AAneta
顧客の声
Runpod の顧客企業の担当者による声。
““Runpod’s not just our infra provider. They’re a partner in what we’re building,” Giacomo said. “They’ve given us the flexibility to grow fast without sacrificing performance or burning cash.””
““The best part? We could stop worrying about infrastructure and go back to building. That’s the real win.””
““That’s when it clicked. We could get the performance we needed without breaking the bank. And because it was serverless, we only paid for what we actually used.””
“We're excited to try Runpod's Clusters because it gives us instant access to high-performing GPU clusters with no long-term commitments.”
“Runpod has allowed us to focus entirely on growth and product development without us having to worry about the GPU infrastructure at all.”
さらに 25 件の声を表示表示を減らす
“Surprisingly, the process of migrating to Runpod was extremely easy and seamless.”
“Having partners like Runpod where we can dream those big ideas and know it's going to happen in the way we're presenting it and selling it to our clients is massive for us.,”
“All of these projects, the renders for AMD, the Coca-Cola builds, that has to do with scalability. If we can't scale, we can't deliver. Runpod makes that possible.”
“I'm in a different time zone. I can literally sleep now instead of getting a call at 3AM. It's on Runpod. It doesn't break. It's fine.”
“When you don't need it, you don't run it, and you don't pay for it. That's all gone now.”
“We use a lot of AWS and GCP, but not for GPU or anything related to GPUs. Whenever we touch a GPU, we're not going there. When it comes to GPU, we're using Runpod,”
“We had physical machines traveling for experiences. They break. They need to be repaired. You get a call at 3AM: the computer broke, what are we doing?”
““Without Runpod, sustaining our business would have been extremely difficult. We truly appreciate it.””
““Runpod gave us a way forward when everything else felt stuck,” one team member reflected. “It’s not just a vendor, it’s part of how we operate.””
““By leveraging Runpod's APIs, we were able to dynamically scale the number of GPU cloud servers according to the live service load,” the team explained. “It allowed us to serve our large-scale infrastructure at nearly half the cost compared to major cloud providers.””
“By leveraging Runpod, we eliminated the infrastructure bottlenecks that slowed us down, and unlocked a cost-effective, high-performance foundation to scale our GenAI platform.”
“We comfortably scaled our workloads 10x without worrying about GPU shortages or excessive costs. That flexibility gave us the headroom to serve enterprise customers with confidence.”
“Runpod’s scalable GPU infrastructure gave us the flexibility we needed to match customer traffic and model complexity, without overpaying for idle resources.”
“Runpod is a great platform for founders like me who want to ship AI models to customers quickly and reliably.”
“Runpod has allowed the team to focus more on the features that are core to our product and that are within our skill set, rather than spending time focusing on infrastructure, which can sometimes be a bit of a distraction.”
“Since switching to Runpod, scalability has been solved in a way that we couldn't do before. We had a very fixed infrastructure, and quickly starting up new containers and new ML services was slow. With Runpod, that process is much faster.”
“The great thing about Runpod is that the pricing becomes a bit more predictable, and we have better unit economics as a business. Whereas if we rolled our own infrastructure, the costs are much more unpredictable, and we end up spending more inefficiently.”
“Moving to Runpod was really smooth. We were using containerized images before, and because Runpod allows us to point to those same images, we were able to move across really easily.”
“We discovered Runpod over a year ago, and to start with, we were just using the pods feature for more ad hoc GPU tasks. Then I noticed that Runpod really was serverless, and that was a big thing for us because it solved a lot of the scalability issues that we were having within our own infrastructure.”
“One issue that we faced was that developers were spending too much time on infrastructure and DevOps. Instead of spending time on product features, we were spending time building this GPU backend.”
“Before using Runpod, we struggled with our AWS infrastructure. Setup wasn't particularly scalable, and we struggled to go from zero instances up to many. We didn't always have the resources on demand in the way that we wanted.”
““Your endpoints can scale down to zero and scale up without a long delay time.””
““After migration, we were able to cut down our server costs from thousands of dollars per day to only hundreds,” the team said.”
““We migrated quickly to Runpod, and all those problems were solved.””
“The main value proposition for us was the flexibility Runpod offered. We were able to scale up effortlessly to meet the demand at launch.”
AI のローンチと提携
Runpod が AI 分野でローンチしたものと協業先。
- ローンチRunpod AI infrastructureRunpod provides AI infrastructure with on-demand GPUs and serverless compute for training, inference, and batch workloads.
- ローンチRunpod ServerlessRunpod Serverless runs AI inference and lets teams deploy containerized models as autoscaling GPU endpoints.
- ローンチRunpod ClustersRunpod offers multi-node GPU environments for distributed training, large batch workloads, and compute jobs, with self-service provisioning for AI workloads.
- ローンチRunpod AI infrastructureRunpod offers AI infrastructure with on-demand GPUs and serverless compute for training, inference, and batch workloads.
求められるスキル
募集中の求人で最も多く見られるもの。
最も求められるスキル
- Python
- Go
- Docker
- Linux systems
- CRM
- Communication
- AI tools
- Data analysis
- Technical writing
- Distributed systems
- Networking
- Distributed storage
技術スタック
- アナリティクス
- Google Analytics 4
- Google Tag Manager
- CDN
- jsDelivr
- Amazon CloudFront
- ライブラリ
- jQuery
- GSAP
- マーケティング
- HubSpot
企業情報
- 本社所在地
- San Francisco, US
- 設立
- 2022
- 業界
- AI Developer Cloud
- 業種(NAICS)
- 情報通信業
- ウェブサイト
- runpod.com
勤務地別の募集
Runpod の採用拠点。都市を選ぶとその募集が表示されます。
Runpod に関する質問
- Runpodは採用中ですか?
- はい。2026年10月9日時点で、Metaintro にはRunpodの募集中のポジションが30 件あります。 過去30日間に9 件が掲載されました。 最も多いのは Developer(4)、Sales(4)、Customer Support(3) です。
- Runpod はどこで採用していますか?
- Runpod は United States、Apac, Uganda、Emea、Surprise、Usa、Uşak, Turkey で採用しており、募集中のポジションが最も多いのは United States です。
- Runpod の顧客にはどのような企業がありますか?
- Runpod は Coframe、Open Source Films、BottoDAO、Faceless.video、Nodalview など 15 社を顧客として挙げています。
- Runpod はどのようなスキルを求めていますか?
- 募集中のポジションで最も多く求められているのは Python、Go、Docker、Linux systems、CRM です。