Clinical Data Annotation Specialist - Sepsis

At CloudFactory, we are a mission-driven team passionate about unlocking the disruptive potential of AI for the world. By combining advanced technology with a global network of talented experts, we make unusable data usable and inference reliable and trustworthy, driving real-world business value at scale.

More than just a workplace, we're a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do, as we strive to connect one million people to meaningful work and build leaders worth following.

Our culture

At CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are:

• Mission-driven: we focus on creating economic and social impact.
• People-centric: we care deeply about our team's growth, well-being, and sense of belonging.
• Innovative: we embrace change and find better ways to do things, together.
• Globally connected: we foster collaboration between diverse cultures and perspectives.

If you're ready to earn, learn, serve, and be part of a vibrant global community, CloudFactory is your place.

About the role

We're looking for US-credentialed clinical professionals to support a specialized clinical data annotation and normalization project focused on Sepsis, using the MIMIC IV de-identified dataset. No prior sepsis specialization is required, we're looking for clinicians who can apply sound clinical judgment and structured annotation guidelines consistently.

In this role, you'll use your clinical expertise to review and interpret de-identified electronic health record (EHR) data, helping ensure that clinical information is accurately annotated, normalized, and structured for downstream use in healthcare technology and AI applications.

This is a hands-on opportunity to apply your clinical knowledge outside of traditional patient care and contribute to a project focused on improving how healthcare data can be understood and used.

We're particularly interested in clinicians with experience in critical care, intensive care, emergency medicine, or other acute-care environments, where familiarity with complex patient presentations and clinical documentation is valuable.

What you'll do

• Review de-identified ICU clinical notes and EHR data related to patients with Sepsis.
• Apply clinical knowledge to interpret and accurately annotate medical information.
• Normalize clinical terminology, concepts, and information within patient records.
• Identify and categorize relevant clinical information according to established annotation guidelines.
• Maintain a high level of accuracy and consistency across annotations.
• Participate in quality assurance and feedback processes to continuously improve annotation accuracy.

Requirements

What We're Looking For

• Current, active US-credentialed Registered Nurse (RN), Nurse Practitioner (NP), or Physician Assistant (PA)
• Strong understanding of clinical terminology and medical documentation.
• Ability to interpret complex clinical notes and EHR information accurately and consistently.
• Strong attention to detail and ability to apply structured guidelines consistently.
• Comfortable working independently in a remote environment.
• Strong written communication skills.
• Ability to commit to approximately 25-40 hours per week.

Preferred Experience

• Experience working in critical care / ICU.
• Experience with Sepsis patients or other acute-care conditions.
• Experience reviewing or working with EHR/clinical documentation.

• Previous experience in clinical research, medical data annotation, clinical informatics, healthcare AI, or similar projects.

Training & Certification

Before beginning project work, selected candidates will complete a required training program. The training is expected to take less than one day and will include certification through PhysioNet.

Engagement Details

Type: Independent Contractor

Time commitment: 25-40 hours per week

Project duration: approximately 3 months 

Working arrangement: Remote, US based

Expected start date: September 15, 2026