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- Tasks: Review and label clinical cases to enhance AI in emergency care.
- Company: Leading AI research organisation focused on clinical intelligence.
- Benefits: Flexible hours, fully remote work, and the chance to shape healthcare technology.
- Why this job: Use your medical expertise to influence the future of AI in healthcare.
- Qualifications: Licensed medical professionals with acute care experience needed.
- Other info: Entry-level role with opportunities for growth in a dynamic field.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We are partnering with a leading research‑focused AI organization developing advanced clinical intelligence systems. We’re seeking licensed medical professionals with hands‑on experience in Emergency Room, Urgent Care, or Acute Care settings to contribute their expertise in evaluating, annotating, and refining medical data for AI development. This role is ideal for clinicians who want to leverage their real‑world patient care experience to shape next‑generation healthcare AI—improving how technology understands acute presentations, triage reasoning, and treatment documentation.
Key Responsibilities
- Review and label clinical cases, documentation, and AI‑generated outputs for accuracy, clinical reasoning, and contextual appropriateness.
- Validate and refine AI‑generated content related to acute care workflows, emergency triage, and differential diagnosis.
- Develop and assess case‑based scenarios reflecting realistic emergency medicine and urgent care encounters.
- Collaborate cross‑functionally with data scientists and clinicians to improve annotation guidelines, ensure consistency, and enhance model reliability.
- Provide expert feedback on alignment with clinical best practices, safety standards, and diagnostic logic.
Ideal Qualifications
- Licensed prescriber (active and unrestricted license in the U.S.) as one of the following: Nurse Practitioner (NP), Physician (MD or DO), Clinical Psychologist (PhD or PsyD, with prescriptive authority), Psychiatrist.
- At least 1 year of post‑licensure clinical experience in Urgent Care, Emergency Room, or Acute Care.
- Demonstrated ability to interpret, document, and evaluate acute clinical scenarios and medical decision‑making.
- Familiarity with electronic medical record (EMR) workflows and documentation standards (e.g., Epic, Cerner, Meditech).
- Exceptional attention to detail and ability to identify inaccuracies or inconsistencies in complex clinical data.
- Strong written communication and documentation skills.
Role Highlights
- Flexible workload: 10–20 hours per week, with potential for up to 40 hours.
- Fully remote and asynchronous—contribute on your own schedule.
- Engage directly with cutting‑edge AI research shaping the future of clinical decision support and emergency medicine documentation.
Job Details
- Seniority level: Entry level
- Employment type: Full-time
- Job function: Research, Analyst, and Information Technology
- Industries: Technology, Information and Internet
Clinical Data Labeling (Emergency & Acute Care Experience) - AI Training employer: Braintrust
Contact Detail:
Braintrust Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Clinical Data Labeling (Emergency & Acute Care Experience) - AI Training
✨Tip Number 1
Network like a pro! Reach out to your contacts in the healthcare and tech industries. Let them know you're on the lookout for opportunities in clinical data labeling. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Get your online presence sorted! Update your LinkedIn profile to reflect your clinical experience and interest in AI. Join relevant groups and engage with posts to show you're active in the field. This can help you get noticed by recruiters.
✨Tip Number 3
Practice your interview skills! Prepare for common questions related to clinical data and AI. Think about how your real-world experience in emergency care can translate into this role. Mock interviews with friends can really boost your confidence.
✨Tip Number 4
Apply through our website! We love seeing applications directly from candidates who are passionate about shaping the future of healthcare AI. Make sure to highlight your hands-on experience in acute care settings when you apply.
We think you need these skills to ace Clinical Data Labeling (Emergency & Acute Care Experience) - AI Training
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your hands-on experience in Emergency Room, Urgent Care, or Acute Care settings. We want to see how your real-world patient care experience can shape the future of healthcare AI!
Be Detail-Oriented: Since this role involves reviewing and labelling clinical cases, it's crucial to demonstrate your exceptional attention to detail. Share examples of how you've identified inaccuracies or inconsistencies in complex clinical data before.
Communicate Clearly: Strong written communication skills are a must! Use clear and concise language in your application to show us that you can effectively document and evaluate acute clinical scenarios.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and get you on board to help shape next-generation healthcare AI!
How to prepare for a job interview at Braintrust
✨Know Your Clinical Stuff
Brush up on your emergency and acute care knowledge. Be ready to discuss specific cases you've handled, as well as how you approached clinical decision-making. This will show that you not only have the qualifications but also the real-world experience they’re looking for.
✨Familiarise with AI Concepts
Since this role involves working with AI, it’s a good idea to understand the basics of how AI in healthcare works. You don’t need to be an expert, but knowing how AI can assist in clinical settings will help you engage in meaningful conversations during the interview.
✨Highlight Your Attention to Detail
Given the importance of accuracy in clinical data labeling, prepare examples that showcase your attention to detail. Discuss situations where you identified inconsistencies or improved documentation processes, as this will resonate well with their expectations.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare thoughtful questions about their AI projects, team dynamics, and how they envision the role evolving. This shows your genuine interest in the position and helps you assess if it’s the right fit for you.