
51 - 200 employees
Founded 2003
🤖 Artificial Intelligence
☁️ SaaS
📋 Compliance
Artificial Intelligence • SaaS • Compliance
Human Signal is a company that specializes in providing a data labeling platform known as Label Studio Enterprise. This platform is designed for automating and refining the data labeling process, integrating capabilities such as natural language processing (NLP) autolabeling, security, quality control, and compliance features. Human Signal focuses on preparing training data, fine-tuning large language models, and evaluating model performance for data science and machine learning teams. They offer a robust API and customizable workflows to optimize the entire AI development lifecycle across various use cases, including legal, medical, and retail sectors. The platform emphasizes secure data handling, being SOC2 certified and HIPAA compliant, ensuring data privacy and integrity.
🕒 April 1
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51 - 200 employees
Founded 2003
🤖 Artificial Intelligence
☁️ SaaS
📋 Compliance
Artificial Intelligence • SaaS • Compliance
Human Signal is a company that specializes in providing a data labeling platform known as Label Studio Enterprise. This platform is designed for automating and refining the data labeling process, integrating capabilities such as natural language processing (NLP) autolabeling, security, quality control, and compliance features. Human Signal focuses on preparing training data, fine-tuning large language models, and evaluating model performance for data science and machine learning teams. They offer a robust API and customizable workflows to optimize the entire AI development lifecycle across various use cases, including legal, medical, and retail sectors. The platform emphasizes secure data handling, being SOC2 certified and HIPAA compliant, ensuring data privacy and integrity.
• Design, build, and operate backend services/APIs in Python/Django with Postgres/Redis. • Own outcomes, not tasks: refine scope, suggest trade-offs, and land increments that deliver value quickly and safely. • Model data and author migrations; tune queries and caching; manage background jobs/queues for high-volume workflows. • Evolve API contracts with FE; keep interfaces clear, versioned, and resilient to change. • Improve reliability and performance (timeouts, retries, idempotency, rate limits, pagination, backpressure). • Implement secure, multi-tenant patterns: auth, permissions/RBAC, auditability, and safe data boundaries. • Contribute to testing strategy (unit/integration), error handling, and graceful failure modes. • Partner with Support to investigate production issues and turn learnings into fixes and prevention. • Engage with our open-source community (issues, discussions) to understand real-world needs and improve developer experience. • Participate in architecture discussions and code reviews; mentor teammates and improve patterns across the codebase.
• Senior-level experience shipping production backends in Python/Django (or a close equivalent) and SQL. • Strong product sense: you’ve made scope/trade-off decisions and iterated based on real-world usage and feedback. • Depth in REST API design, relational modeling, migrations, and performance tuning. • Experience with background processing/queues (e.g., Celery/RQ/Kafka-backed workers) and operational concerns. • Clear written communication at a Senior IC level—concise RFCs/PRDs, actionable reviews, and crisp decision records. • Nice to have: GraphQL familiarity; Kafka/streaming; Spark/BigQuery; security/compliance exposure; multi-region architectures.
• Regional compensation market rate ranges • Base cash compensation
Apply Now🕒 April 1
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