解决方案架构师
Solutions Architect
HumanSignal 是一家为构建 AI 模型和产品的公司提供真实世界数据的合作伙伴。我们的客户因为与我们合作，从真实数据创建到标注再到交付，能够更快地打造更优秀的 AI 产品。
我们从零开始设计和创建数据集，招募并管理评估模型输出的领域专家，并通过我们自己的平台 Label Studio 进行所有工作。Label Studio 是一个开源的数据标注和评估标准，全球有超过一百万的从业者在使用。
我们专注于操作复杂的领域：真实世界的数据收集、多模态流程和多步骤工作流。高级 ML 和 AI 团队使用我们的企业级平台运行他们自己的数据工厂，当内部能力不足时，也会借助我们的服务团队扩展他们的能力。
如果你希望参与塑造下一代 AI 产品的发展，我们期待与你交流。
关于这个机会：
我们正在寻找一位解决方案架构师加入我们不断壮大的营收团队。在这个职位上，你将负责整个客户生命周期的技术关系，从售前到售后。
你将成为我们最重要的企业客户背后的技术伙伴，从初次沟通到生产规模。与客户经理一起，你将主导技术调研、定制演示、架构评审和概念验证，然后将同样的解决方案带入上线、流程设计、集成和持续优化。在整个 Label Studio Enterprise 的旅程中，你将是客户值得信赖的技术顾问。
Label Studio 是一个高度技术性的产品，被数据科学家和 ML 工程师作为核心基础设施使用。在这里取得成功，你需要真正理解数据标注及其对模型性能的作用。你将直接与 ML 工程师、数据科学家和 MLOps 团队合作，构建能够在生产环境中经受考验的解决方案。
你将负责：
- 与客户经理合作处理战略性交易，主导技术调研、定制演示、架构评审和概念验证，以证明 Label Studio Enterprise 在真实客户数据和工作流中的价值。
- 推动技术上线，指导客户完成安装、安全配置以及在云、本地或混合环境中的最佳实践部署。
- 构建 Label Studio 与客户 AI/ML 工作流、流程和存储系统之间的集成。
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About HumanSignal
Real-world data is the competitive edge in AI.
HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.
We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.
We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.
If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk.
About the Opportunity:
We're looking for a Solutions Architect to join our growing revenue organization. In this role, you'll own the technical relationship across the entire customer lifecycle, pre-sale through post-sale.
You'll be the technical partner behind our most strategic enterprise accounts, from first conversations through production scale. Working alongside Account Executives, you'll lead technical discovery, demos, and proof-of-concepts, then carry that same solution through onboarding, workflow design, integration, and ongoing optimization. You'll be your customers' trusted technical advisor at every stage of their Label Studio Enterprise journey.
Label Studio is a deeply technical product, used by Data Scientists and ML Engineers as core infrastructure for their work. To succeed here, you'll need a real understanding of data labeling and the role it plays in model performance. You'll work directly with ML Engineers, Data Scientists, and MLOps teams to architect solutions that hold up in production.
What You’ll Do:
- Partner with Account Executives on strategic deals, leading technical discovery, tailored demos, architecture reviews, and proof-of-concepts that prove out Label Studio Enterprise against real customer data and workflows.
- Drive technical onboarding, guiding customers through installation, secure configuration, and best-practice deployment across cloud, on-prem, or hybrid environments.
- Architect integrations between Label Studio and customer AI/ML workflows, pipelines, storage, and enterprise systems.
- Build custom solutions (scripts, plug-ins, and APIs) to extend Label Studio for unique customer requirements.
- Serve as the senior technical escalation point for your accounts, resolving advanced issues and collaborating with Product, Engineering, and Support.
- Deliver enablement, workshops, and documentation that make customer teams self-sufficient on the platform.
- Act as a trusted technical advisor to customer engineering, data, and AI/ML teams, supporting adoption, expansion, and long-term value.
What You'll Bring:
- 5+ years in a customer-facing technical role (Solutions Architect, Sales Engineer, Professional Services Engineer, or similar) for a highly technical product, ideally enterprise SaaS or ML/AI platforms. Experience on both sides of the sale is ideal.
- You've built a data labeling pipeline yourself, whether that's data annotation, labeling workflows, or the broader ML lifecycle. You can explain how it works to an engineer and to a VP without changing much.
- Hands-on work integrating SaaS platforms with ML pipelines. You've deployed models to production, or done the engineering to get datasets ready for data science teams.
- Fluency in Python, REST APIs, and infrastructure tools (Linux/Unix, Docker; Kubernetes a plus). You've built against multiple client APIs and SDKs. JavaScript, CSS, and HTML are a plus.
- A track record of running technical discovery, demos, and proof-of-concepts during the sales cycle, then owning onboarding, implementation, troubleshooting, and custom development after the close.
- Enough business sense to go with the technical depth. You can take a customer's problem and hand it back to them as a value proposition they actually recognize, and you can see an objection coming before it lands.
- Executive presence and sharp writing, with the range to move between Data Scientists, ML Engineers, and technical executives.
- Comfortable juggling multiple complex accounts and competing priorities.
We are hiring for this role across North America. Base Salary is targeted between $122,500 - 143,500 USD (based on experience and skills). This role also qualifies for variable compensation; anticipated On-Target Earnings if an employee is meeting objectives are $175,000 - $205,000 USD. This range is provided by market data and is in good faith. Final offer details are determined by several factors including candidate experience, expertise as well as applicable industry knowledge, and may vary from the pay ranges listed above. We also offer stock options, comprehensive health benefits, and a strong team culture rooted in transparency and collaboration. Join us!