AI Trainer – Medical (Nurses, Advanced Practice, Physicians, Pharmacists)

Planet Pharma; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

Planet Pharma is seeking experienced clinicians to evaluate frontier AI models in real clinical work. You will design realistic tasks such as SOAP notes, reconciliations, triage decisions, discharge summaries, patient education, or protocols, and run them through frontier AI agents to assess performance against professional standards.

You will work with real-world clinical files you assemble yourself, ranging from compact to multi-day scenarios, aiming to push AI to meet expert-level judgments

Qualifications

• Active or recent clinical license (RN, NP, PA, MD/DO, PharmD or allied health).
• 2+ years hands-on clinical practice preferred; qualified regardless of experience with practical work.
• Able to draw on real-world experience and day-to-day workflows to craft scenarios.
• Hands-on practitioner, not only managerial roles.
• Excellent written and spoken English at a professional level.
• Familiarity with AI/LLM tools and ability to judge AI outputs.
• Baseline tech literacy: Google Workspace and basic file handling.
• Available at least 10 hours per week; no weekly maximum.
• Based in United States, Canada, or the UK.

Responsibilities

• Design realistic clinical tasks drawn from day-to-day practice.
• Run tasks through frontier AI models and evaluate outputs against professional standards.
• Compare model outputs and document performance gaps.
• Write grading rubrics detailing deliverables and reasoning.
• Flag concrete failures with evidence and reasoning.
• Refine tasks and review tasks created by other clinicians.

Skills

Clinical practice

English proficiency

Attention to detail

Critical thinking

Documentation literacy

AI/LLM familiarity

Education

Bachelor’s degree or higher

Tools

Google Workspace

AI/LLM tools (e.g., Claude, ChatGPT)

Job description

About the role

is looking for experienced clinicians to evaluate how frontier AI models handle real clinical work: an assessment and plan from a history and exam, a medication reconciliation with interaction checks, a triage decision, a discharge summary, patient education, or a clinical protocol. You bring the judgment you have built co signing a resident’s note only after fixing the plan, catching the interaction the order set missed, and knowing when a presentation does not fit the obvious diagnosis. We bring the model output that judgment is needed to grade.

In this role, you will design challenging, realistic tasks drawn from your own practice, such as a SOAP note and plan for a constructed case, a medication reconciliation with interaction review, a triage decision with rationale, a discharge summary, a patient education handout, or a clinical protocol or standing order set, run them through frontier AI agents, and evaluate what comes back against a professional standard.

You will work with realistic professional files, the kind a practitioner in your field actually handles, which you assemble yourself. Some tasks are compact, built around a handful of files; others are larger scenarios that take several days to build. In every case the goal is the same: a task a competent professional in your field would complete correctly and a frontier model currently gets wrong.

This is not a traditional clinical role. You will be helping build better AI by putting your knowledge to work in a structured, flexible, fully remote environment. The work is long form and self directed, and clear written reasoning matters as much as technical depth.

Responsibilities

• Design challenging, realistic clinical tasks drawn from your own day to day practice: the scenario, a prompt phrased the way you would brief a trusted colleague, and the supporting files a clinician would need (constructed or de identified histories, exam findings, labs, imaging reports, medication lists, prior notes), which you author yourself.
• Run those tasks through frontier AI models and evaluate the deliverable they produce (the note, plan, reconciliation, summary or protocol) against the standard you would hold a colleague to.
• Compare two model outputs on identical prompts and files, decide which performed better, and document where each fell short.
• Write detailed grading rubrics that specify what a correct deliverable must contain, such as the right differential considered, the right red flags addressed, the right medication decisions, the right communication for the recipient, and explain in writing why a response passes or fails each one.
• Flag concrete failures with evidence: unsupported assessments, missed contraindications or interactions, anchoring on the obvious diagnosis, fabricated or ignored data, unsafe or inappropriate communication, and off brief interpretation of the ask.
• Contribute across your setting and adjacent ones, and review and refine tasks built by other clinicians.

Domain qualifications

• 2+ years of current or recent hands on clinical practice preferred. In progress Bachelor’s degree or higher.
• Licensed clinician: RN, NP, PA, MD or DO, PharmD, or an allied health license with independent clinical judgment (for example respiratory therapy, physical therapy, midwifery). Licensed candidates may be asked to verify licensure during the assessment.
• Depth in at least one setting or specialty: acute care and med surg, emergency, critical care, primary care and family medicine, pediatrics, obstetrics, behavioral health, geriatrics and long term care, perioperative, oncology, pharmacy.
• Working understanding of adjacent settings, enough to know what those workflows involve and how they are run, so you can assess work outside your own unit and point out what was done correctly or incorrectly.
• Reads and writes clinical documentation at a practitioner level and grounds decisions in current guidelines and the patient context rather than habit.

General requirements

• Active or recent clinical license: RN, NP, PA, MD or DO, PharmD, or an allied health license with independent clinical judgment.
• 2+ years of hands on experience in your field preferred (see Domain qualifications above). Candidates with less experience are considered where the practical work is real.
• Able to draw on your own real world experience and day to day workflows to craft scenarios that test whether an AI system can actually do the work.
• Hands on practitioner: you currently do (or recently did) the work yourself at an individual contributor level, not solely in a managerial capacity.
• Full professional or native level written and spoken English, with strong written communication. You can explain complex professional reasoning clearly and concisely, and articulate why a result is wrong, not only that it is.
• Comfort with ambiguity and attention to detail. You can orient in a new set of files and build an accurate, deep working picture of it quickly, especially when the subject sits partly outside your own specialization. You verify what a document claims against the underlying numbers, sources or facts.
• Capable of interpreting feedback, judging which parts of it are actually correct, and applying it without hand holding. When stuck, you look for the answer rather than waiting for one.
• Ability to ramp quickly on unfamiliar work from written material and instructions alone, including where that material is incomplete (for example, writing grading rubrics for the first time).
• General familiarity with AI and LLM tools. You have used models like Claude or ChatGPT in professional work and have the judgment to tell a well reasoned answer from a plausible sounding but incorrect one.
• Baseline tech literacy: comfortable with cloud file tools (e.g., Google Workspace), managing browser profiles, downloading and installing desktop apps (e.g., Claude), and everyday file handling (e.g., converting between Excel and Google Sheets, zipping files for sharing).
• Available at least 10 hours per week, with no weekly maximum. Consistent availability is valued and full time hours are available.
• Based in the United States, Canada, or the UK.