Why This Job is Featured on The SaaS Jobs
This listing stands out in the SaaS landscape because it sits at the intersection of subscription software and applied AI in healthcare. Sensi.AI’s product is positioned as an always-on virtual assessment tool, which typically depends on reliable data pipelines and consistent annotation standards to keep models aligned with real-world usage. A clinical data labeling role in this context is a direct lever on product quality, especially when the software is designed to surface alerts and insights from unstructured inputs like speech and ambient sounds.
From a SaaS career perspective, the work builds fluency in how AI-enabled SaaS products are maintained and improved after launch: creating training-ready datasets, tightening labeling guidelines, and iterating with technical stakeholders. That experience translates across many SaaS environments where ML features are embedded into the core application and operational rigor is required to keep outputs dependable over time.
This role is best suited to professionals who enjoy precision work, can apply clinical judgment consistently, and prefer structured workflows with clear quality bars. It also fits someone comfortable collaborating with an AI team and communicating edge cases and guideline gaps, particularly in an on-site setting where feedback loops can be tight and frequent.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Description
Join Our Mission at Sensi.AI
At Sensi.AI, we are dedicated to creating a world where every older adult receives the care they truly deserve. Guided by compassion and driven by innovation, we aim to redefine the future of caregiving. If you’re passionate about making a meaningful impact, join us in advancing Sensi.AI’s virtual assessment tool. This cutting-edge technology monitors seniors' health in their homes 24/7, delivering emergency alerts, actionable insights, and predictive analysis to enable proactive and effective care.
Here, you’ll discover exciting opportunities for professional growth, make a direct and meaningful impact on our products and company, and contribute to a mission that truly matters.
About The Role
The Clinical Data Labeler contributes significantly to the training of our AI models, which aim to enhance the quality of life for senior citizens. This position involves meticulously tagging and classifying textual data based on clinical and technical criteria to ensure high-quality AI training datasets.
Key Responsibilities:
- Review and analyze textual data, including speech and other relevant sounds.
- Accurately tag and classify textual data using clinical and technical criteria.
- Collaborate with the AI team to refine and improve labeling guidelines.
- Communicate regularly with the team to report challenges, suggest improvements, and ensure consistent data labeling.
- Maintain a high level of attention to detail to ensure quality and accuracy in data labeling.
Requirements
- Clinical Knowledge & Experience: You have a background in clinical work or relevant academic studies (e.g., nurse, paramedic, medical student) and can apply your expertise to data labeling and classification.
- Language Proficiency: You are fluent in English at a native or near-native level, with strong written and verbal communication skills. Spanish proficiency is an advantage.
- Goal-Oriented & Detail-Focused: You are highly motivated, able to meet deadlines, and work efficiently while maintaining accuracy and attention to detail.
- Digital Literacy: You are comfortable working with digital tools and AI-driven platforms, adapting quickly to new technologies and workflows.
- Team Player & Collaborative Mindset: You work well in a team-oriented environment, contributing to shared goals while maintaining clear and open communication.
- Customer-Centric Approach: You are dedicated to customer success, ensuring high-quality outputs that align with the company’s mission and values.
