高性能计算基础设施工程师 - GPU 集群
HPC Infrastructure Engineer - GPU Clusters
关于ElevenLabs
ElevenLabs是一家AI研究和产品公司，正在改变我们与技术互动的方式。
我们于2023年1月推出首个类人AI语音模型。如今，我们为数百万用户和数千家企业服务——从快速发展的初创公司到德意志电信和Meta等大型企业。我们的投资人包括世界上最著名的投资机构，如Andreessen Horowitz、ICONIQ Growth和Sequoia。我们已筹集7.81亿美元资金，上一次估值为110亿美元——始终与11有关。
我们已从语音扩展到三个主要平台：
- ElevenAgents帮助企业在部署语音和聊天代理时实现无缝且智能的客户体验，提供必要的集成、测试、监控和可靠性。
- ElevenCreative赋予创作者和营销人员在70多种语言中生成和编辑语音、音乐、图像和视频的能力。
- ElevenAPI让开发者可以访问我们领先的AI音频基础模型。
我们所做的每一件事都是团队创造力和奉献精神的结果——建设者们正在做他们一生中最好的工作。我们是研究人员、工程师和运营人员。IOI奖牌获得者和前创始人。如果你想要努力工作并创造持久的积极影响，我们想听你讲述。
我们如何工作
- 高速度：快速实验，精简的自主团队，以及最小的官僚主义。
- 以影响而非职位名称来衡量：我们没有职位名称。而是看你的影响。没有任何任务高于或低于你。
- AI优先：我们使用AI以更高的质量更快地完成工作。我们在整个公司都这样做——从工程到增长再到运营。
- 无处不在的卓越：我们所做的每件事都应该与我们的AI模型质量相匹配。
- 全球化团队：我们重视你的才能，而不是你的位置。
我们提供的福利
- 创新文化：你将参与一个世代性的机会，定义AI的发展方向，身边有不断突破可能性边界的团队。
- 成长路径：加入ElevenLabs意味着加入一个充满活力的团队，有无数机会推动影响力——超越你当前的角色和职责。
- 学习与发展：ElevenLabs主动通过年度可支配津贴支持职业发展。
- 社交旅行：我们还提供年度可支配津贴，让你每年以自己喜欢的方式与同事见面。
- 年度公司集训：每年，我们都会在新的地点将整个团队聚集在一起。
查看英文原文
ABOUT ELEVENLABS
ElevenLabs is an AI research and product company transforming how we interact with technology.
We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always.
We have expanded from voice into three main platforms:
- ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.
- ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.
- ElevenAPI gives developers access to our leading AI audio foundational models.
Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.
HOW WE WORK
- High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.
- Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.
- AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.
- Excellence everywhere: Everything we do should match the quality of our AI models.
- Global team: We prioritize your talent, not your location.
WHAT WE OFFER
- Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.
- Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities.
- Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.
- Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.
- Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy.
- Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.
ABOUT THE ROLE
Every model we train runs on infrastructure this role owns. We operate NVIDIA GPU clusters across bare metal and rented capacity, and we're looking for an engineer to join our small research infrastructure team and make that compute fast, reliable, and boring - in the best sense. When the clusters just work, research moves faster. Your impact is measured directly in training throughput and researcher velocity.
This is a builder-operator role with real breadth: one week you're writing automation that eliminates a whole class of manual work, the next you're benchmarking a new provider's InfiniBand fabric or on-site bringing new hardware online. You'll have unusual scope and autonomy - we're a lean team where decisions are made by the people closest to the problem.
WHAT YOU’LL BE DOING
- Operate and improve our GPU fleet end to end: provisioning, scheduling, monitoring, upgrades, capacity planning
- Build automation that keeps the fleet healthy without human intervention — node health checks, automated draining and remediation, burn-in pipelines for new capacity
- Own the stack beneath the training code: OS images, NVIDIA drivers, CUDA, container runtimes, NCCL, high-speed networking (InfiniBand/RoCE)
- Run and tune job scheduling (Slurm or similar) so researchers get compute fairly and fast
- Build and maintain high-performance storage for datasets and checkpoints
- Hunt down performance problems: stragglers, degraded links, thermal issues, flaky GPUs — and fix the class of problem, not just the instance
- Evaluate rented GPU capacity: benchmark it, validate it, hold providers to their SLAs
- Hands-on hardware work when it's needed: racking, cabling, diagnostics, coordinating with datacenter staff and vendors
- Keep clusters secure by default: access control, network isolation, secrets
REQUIREMENTS
- Have run large-scale Linux server or GPU environments in production and enjoy both building and operating
- Know the NVIDIA stack well — drivers, CUDA, NCCL, DCGM — or have deep systems experience and learn hardware stacks fast
- Are comfortable with bare-metal environments, server hardware, and high-speed networking
- Write solid automation in Python and/or Bash, with IaC tools like Ansible or Terraform
- Are happy digging into noisy data (metrics, logs, PromQL) to find what's actually wrong
- Like owning real scope end to end and being the person others rely on
- Don't consider any task above or beneath you — datacenter trips included
NICE TO HAVE
- Experience supporting ML training workloads from the infra side (distributed training failure modes, checkpointing patterns)
- Experience evaluating and working with GPU cloud providers
- Parallel filesystems (WEKA, VAST, etc) or large-scale object storage
- BMC/IPMI/Redfish automation, PXE provisioning at scale
- Power and cooling awareness for dense GPU deployments
LOCATION
This role is remote and can be executed globally. If you prefer, you can work from our offices in London, New York, San Francisco, and Warsaw.
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We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.