​This is a full-time Support Engineer role at HumanSignal, a company building the platform (Label Studio) that powers the creation, curation, and evaluation of high-quality data for AI/ML workflows. This role is crucial for providing technical support to enterprise clients using the open-source and enterprise versions of the data labeling software.

• ​Location: Remote – Europe or East Coast North America.
• ​Compensation (US Base Cash Range): $75,000 to $90,000 USD (Note: Compensation based on regional market rate ranges across the globe).
• ​Experience Required: 3–5 years in technical support or support engineering for a SaaS or developer-focused product.
• ​Focus: Debugging and troubleshooting issues related to the installation, configuration, and usage of the Label Studio platform, which involves cloud environments, containers, and APIs.
• ​Key Contribution: Advancing the support maturity by improving processes, contributing to internal tooling, and enhancing self-service documentation.

​Responsibilities: Diagnosis, Collaboration, and Maturity

​The Support Engineer is a technical expert and key collaborator responsible for ensuring the seamless operation of the platform for clients building mission-critical AI pipelines.

• ​Client Support: Provide technical support to clients via email and support tickets, addressing inquiries related to the installation, configuration, and usage of Label Studio.
• ​Troubleshooting: Diagnose and troubleshoot software issues reported by clients, utilizing debugging tools and logs to identify root causes and implement timely resolutions.
• ​Collaboration & Escalation: Collaborate closely with Product, Engineering, and Customer Success to drive issue resolution, providing structured, high-quality customer updates throughout investigations.
• ​Documentation & Process: Create internal and external documentation to improve support quality and self-service. Proactively identify opportunities for process improvements and contribute to the continuous enhancement of support procedures and workflows.
• ​Technical Breadth: The platform supports multiple modalities (text, images, time series, agents-in-environments), requiring the ability to quickly grasp issues across different data types.

​Required Technical Requirements and Qualifications

​The ideal candidate has a strong background in the cloud-native development stack, proficiency in a scripting language, and an understanding of machine learning concepts.

• ​Experience: 3–5 years in technical support for a SaaS or developer-focused product.
• ​Debugging Skills: Strong debugging skills across cloud environments, APIs, browser issues, and containerized systems.
• ​Cloud & DevOps:
  • ​Strong understanding of cloud computing platforms, particularly AWS (Amazon Web Services), including services such as EC2, S3, Lambda, and IAM.
  • ​Preferred: Experience with Kubernetes, container orchestration, or infrastructure debugging.
• ​Programming: Proficiency in Python or JavaScript programming language for scripting and automation tasks.
• ​AI/ML Domain:
  • ​Familiarity with machine learning concepts and frameworks, with experience working with ML models preferred.
  • ​Preferred: Knowledge of ML/AI workflows or data labeling pipelines.
• ​Soft Skills: Exceptional communication skills (written and verbal), excellent problem-solving ability, and a customer-centric approach.