Domain Expert – Python

HumanitApp; United States; Remote; USD 276,000 - 372,000; Full time

Benefits offered by this job

Flexible remote work

Pay Per Task

NDA required

Contract extension potential

Job summary

Turing is hiring US-based academic dermatologists to contribute senior clinical expertise to data curation for frontier AI models and labs. This is the senior reviewer track of the project, designed for dermatology faculty who want to apply academic expertise to rigorous AI evaluation.

The role is fully remote as an independent contractor (1099), with an anticipated average of 15 hours per week (up to 40 during peak batches) and a 4-week engagement.

Qualifications

• Board-certified in dermatology and licensed to practice in the US.
• Fellowship training in dermatology subspecialties is valued.
• Strong publication record and academic appointment preferred.

Responsibilities

• Lead senior-level clinical review on complex or ambiguous cases.
• Develop and document clinical evaluation frameworks.
• Provide expert advisory hours to client teams reviewing AI outputs.
• Publish guideline-aligned clinical commentary as needed.

Skills

Clinical review leadership

Written clinical reasoning

Educator experience

Client communication

IRB/Research committee service

Education

Board-certified in Dermatology

Active medical license in US state

Subspecialty fellowship training (dermatopathology, Mohs/procedural, pediatric, or complex medical dermatology)

Publication record in peer-reviewed dermatology journals

Faculty appointment at US medical school or academic medical center

Tools

Clinical AI evaluation exposure

Regulatory/compliance awareness

Job description

Future projects, not immediate vacancies. Check each network's country and experience requirements.

We are hiring US-based academic dermatologists to contribute senior clinical expertise to data curation for frontier AI models and labs. The work supports a longitudinal dermatology dataset used by AI developers, regulatory teams, and academic groups. This is the senior reviewer track of the project. You will lead clinical review on complex cases, contribute to the development of clinical evaluation frameworks, and serve as expert advisor for client teams reviewing AI model outputs.

Official job description checked 2026-10-24:

About Turing:

Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality data, evaluations, and reinforcement learning environments that improve model capabilities in coding, reasoning, tool use, and multimodality. In coding, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across Financial Services, Life Sciences, Healthcare, Retail, Automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models.

Role Overview:

We are hiring US-based academic dermatologists to contribute senior clinical expertise to data curation for frontier AI models and labs. The work supports a longitudinal dermatology dataset used by AI developers, regulatory teams, and academic groups. This is the senior reviewer track of the project. You will lead clinical review on complex cases, contribute to the development of clinical evaluation frameworks, and serve as expert advisor for client teams reviewing AI model outputs.

The role is designed for dermatology faculty who want their academic expertise to count toward something rigorous, and who are interested in AI evaluation, methodology, and the durable infrastructure of clinical AI.

What You’ll Do Day-to-Day:

Lead senior-level clinical review on complex or ambiguous cases.

Facilitate structured resolution of clinical disagreement among reviewers.

Contribute to the development of clinical evaluation frameworks.

Provide expert advisory hours to client teams reviewing AI model outputs

Author guideline-aligned clinical commentary on cases as needed.

Provide subspecialty consultation as appropriate

Requirements:

Faculty appointment at the rank of Assistant Professor or above at an accredited US medical school or academic medical center

Minimum 3 years post-residency completion

Board-certified in dermatology by the American Board of Dermatology

Active medical license in good standing in at least one US state

Active clinical practice

Subspecialty fellowship training (dermatopathology, Mohs/procedural, pediatric, or complex medical dermatology).

Publication record in peer-reviewed dermatology journals.

Prior exposure to clinical AI evaluation, digital health, or dermatology AI research (desired).

Active involvement with AAD, ASDS, or other dermatology specialty societies.

Prior journal peer review experience Prior IRB or research committee service.

Experience teaching residents or fellows.

Deep familiarity with current dermatology guidelines.

Strong written articulation of clinical reasoning suitable for peer review

Ability to lead and document clinical consensus

Comfort with graphic medical images and clinical complexity

Disciplined adherence to project protocols

Perfomance Expectations:

Senior reviewer responsibility on assigned case batches.

Clinically defensible documentation.

Consistent reliability with peer faculty reviewers

Constructive client-facing communication during advisory hours.

Conflict of interest disclosure.

Applicants will be asked to disclose any active equity, advisory, consulting, or paid relationships with dermatology AI companies, digital health platforms, or pharmaceutical companies whose products may appear in case content.

Disclosed conflicts do not automatically disqualify applicants but will be considered in case assignment.

Perks of Freelancing with Turing:

Competitive pay and flexible remote work.

Learn how advanced AI systems are trained.

Be part of cutting-edge projects with top LLM companies.

Potential for contract extension.

Freelance perks: flexibility, global collaboration, and future-proof skills.

Independent contractor (1099): Compensation determined based on years of experience, academic standing, and clinical expertise Anticipated average 15 hours per week; up to 40 hours per week during peak batches.

Engagement type: Pay Per Task.

Project and assignment dependent timeline.

NDA required upon engagement; detailed scope of work shared after NDA execution.

Fully remote and asynchronous, with occasional synchronous calls.

Duration: 4 weeks

Evaluation Process:

To apply Submit CV (including faculty appointment details), two recent peer-reviewed publications, and a brief statement of interest (300 words) describing your experience with structured clinical writing or AI evaluation. Successful applicants will complete a brief paid calibration assignment before full engagement.

Shortlisting based on qualifications and one round of interview.

Confirm current eligibility, workload and final terms with Turing. Referral rewards are separate from applicant compensation.

Python

Compensation context

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• Ability to lead and document clinical consensus

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