The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data.
At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise.
Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems.
Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk.
This is a product-engineering role: not “build what you’re told,” but shape what we build—own the problem, propose solutions, and ship outcomes that matter to users and the business.
We’re hiring a Senior Frontend Engineer with product vision. You’ll lead with craft—shipping fast, accessible UX in React/TypeScript—and partner early with PM/Design to frame problems, prototype to learn, and make pragmatic scope calls. You care about clarity, performance, and simplicity in complex, data-heavy workflows—so the result feels simple, performant, and trustworthy.
Python/Django, JS/TS, React, OpenAI API, Spark, BigQuery, Kafka, Jest, Cypress, AWS, Kubernetes, Postgres, Redis.
Trunk-based development with small, reviewable PRs; feature flags for safe rollouts; strong code reviews; pragmatic testing; and close collaboration with Product/Design/Support.
At HumanSignal, we follow a six-week cycle known as "Build and Ship" followed by a "Cooldown." During the first four weeks, the team focuses on creating new features and shipping improvements. We also rotate a small group to handle customer support, ensuring everyone stays in touch with real user needs and we can respond quickly to issues.
After those four weeks, we have a two-week "Cooldown" period. This is when we tackle technical debt, refine our integration processes, and wrap up those lingering tasks that never quite fit into regular sprints but really help us feel good about our codebase and workflows.
At HumanSignal we pay based on regional compensation market rate ranges across the globe. We are hiring for this role across North and South America as well as Europe. The base cash compensation range is $140,000 to $200,000 USD. These ranges are provided by market data and are in good faith. The 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.
It is an exciting time at HumanSignal, we are a growing startup and at this stage we are constantly evolving. While we have put a lot of thought into your first and most important initiatives, it’s only an example and something we will work on together. We're always learning and growing, so like us this role will evolve and expand. We hope that this opportunity sounds exciting to you and that you consider joining us on our journey!
We build software that helps people do what only they can do – give meaning. Data fills our modern world. It flows prolifically inside organizations, customer interactions, product usage, environmental research, healthcare imaging, and beyond. What if we could use any of this historical data to predict the future? In most cases, we can now make predictions through Machine Learning & AI, but to do so in a meaningful and impactful way, historical data needs to be accurate, comprehensive, and without bias. To make the best predictions, we believe teams with domain expertise should be responsible for annotating and curating data. It's called data labeling, and it’s a process of real people giving meaning to the information they see on the screen. HumanSignal was founded to take data labeling operations to the next level and help data scientists make better predictions.
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