Member of Technical Staff, Translational Medicine

Sci.bio Recruiting; San Francisco (CA); On-site; USD 250,000 - 400,000; Full time

Benefits offered by this job

Equity

401(k) contributions

Meals provided

Conference travel

Fully covered health plan

Job summary

Sci.bio Recruiting seeks a physician-lead to guide AI benchmarks evaluating clinical reasoning in drug development and translational science. You will translate clinical endpoints into robust evaluation tasks and ensure AI conclusions align with medical practice and regulatory expectations.

The role involves building strategic clinical datasets, negotiating data-use agreements, and mentoring an emerging clinical analytics team while partnering with researchers, patient groups, and biopharma

Qualifications

• MD with residency training and clinical leadership experience.
• Experience selecting, developing or defending clinical endpoints in clinical trials (Phase I–III).
• Strong understanding of FDA interactions and regulatory documentation.

Responsibilities

• Lead selection and development of translational and clinical endpoints for AI benchmarks.
• Convert real-world programs into evaluation tasks for AI systems.
• Serve as senior clinical SME across therapeutics, omics, and biosecurity.
• Develop data partnerships with patient organizations, healthcare systems, and biotech firms.
• Lead data-use agreements, informed consent, de-identification, and privacy processes.
• Help establish the clinical function and recruit internal team members.

Skills

Clinical development expertise

Regulatory strategy

Data partnerships

Clinical data governance

Education

MD degree

Tools

dbGaP access

IRB processes

Job description

This role sits at the intersection of clinical medicine, drug development, translational science, and artificial intelligence. The individual will provide clinical leadership in developing benchmarks used to evaluate how effectively advanced AI systems can reason through complex biological, therapeutic, and medical problems. A major focus of the position will be determining which clinical and translational outcomes are most meaningful when assessing AI performance. This person will use their experience as a physician and clinical investigator to determine whether AI-generated conclusions are medically sound and relevant to clinicians, researchers, and regulators. The role will also be responsible for helping identify and secure high-value clinical datasets used to develop these evaluations. Much of this information may come from non-public sources, including historical clinical trials, patient registries, healthcare organizations, research institutions, nonprofits, and biotechnology companies. Success will require strong relationship-building skills as well as an understanding of the agreements, privacy requirements, and compliance processes involved in working with sensitive clinical data.

Responsibilities:

• Lead the selection and development of translational and clinical endpoints for therapeutic and disease-focused AI benchmarks, taking responsibility for the scientific and clinical rationale behind those decisions.
• Convert real-world drug development programs and clinical trial designs into structured evaluation tasks that can be used to measure the performance of AI systems. This includes drawing insights from both successful and unsuccessful clinical programs, particularly when the reasons behind trial outcomes are well understood.
• Serve as a senior clinical subject-matter expert across areas such as therapeutics, omics, and biosecurity, providing final clinical review of disease- and treatment-related conclusions.
• Develop strategic data and research partnerships with patient organizations, nonprofit groups, healthcare systems, academic institutions, biotechnology companies, and other organizations that maintain valuable clinical datasets.
• Lead the development and execution of data-use agreements and establish appropriate processes around informed consent, de-identification, regulatory compliance, privacy, and review of sensitive clinical information.
• Help establish and expand the clinical function, initially working alongside external clinical and scientific advisors and eventually recruiting and developing an internal team.

Minimum Qualifications:

• MD degree with completed residency training.
• Direct experience selecting, developing, evaluating, or defending clinical endpoints within a Phase I, Phase II, or Phase III clinical trial.
• Experience serving as a physician or named investigator on at least one Phase I–III clinical study.
• Strong understanding of clinical drug development, including mechanism of action, patient selection, dosing strategy, safety considerations, endpoint selection, and interactions with the FDA or safety monitoring committees.
• Experience preparing or contributing substantially to FDA regulatory documentation, such as IND submissions, clinical trial protocols, investigator brochures, BLA/sBLA filings, or medical device authorization materials.
• Strong understanding of disease biology and progression, with the ability to connect clinical phenotypes to potential molecular or genetic mechanisms.

Preferred Qualifications:

• Clinical development or research experience within rare diseases, oncology, solid tumors, gene therapy, or related therapeutic areas.
• Familiarity with evaluating the capabilities and limitations of advanced AI models, particularly within biological, scientific, or clinical applications.
• Hands‑on experience taking data‑use agreements from initial discussions through execution.
• Strong knowledge of patient consent, clinical data de‑identification, IRB review, and the processes required to responsibly use sensitive healthcare information.
• Experience establishing research or data partnerships with patient advocacy groups, nonprofits, academic medical centers, healthcare systems, biotechnology companies, or similar organizations.
• Familiarity with clinical data privacy and governance frameworks, including HIPAA and GDPR, as well as NIH controlled‑access resources such as dbGaP and Data Access Committees.
• Experience incorporating AI tools into clinical, scientific, or research workflows, along with an understanding of where current AI systems perform well and where their limitations become clinically significant.

Compensation and Benefits:

• Total compensation ranges from $250,000 to $400,000, depending on clinical and technical experience.
• We believe in long‑term incentive plans and provide equity and 401(k) contributions.
• Benefits include health plan with 100% of premiums covered, no deductible, and no out‑of‑pocket costs.
• Daily meals, including lunch and dinner, are provided. Travel and accommodations for medical conferences or other professional networking trips are included.