Scientist, Cell and Gene Therapy (AI Research)

RecruitSeq; United States; Remote; USD 140,000 - 180,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

RecruitSeq is seeking a Scientist, Cell and Gene Therapy (AI Research) in San Francisco or remote to join a team that evaluates how AI supports decisions in cell therapy, gene therapy, and RNA drug programs. This is a full-time W2 position with benefits and equity.

The ideal candidate has an MS or PhD with direct experience on therapeutic programs and can explain how experimental results guided the next steps. Collaboration with scientists and engineers to assess AI agents is essential.

Qualifications

• MS/PhD or equivalent professional experience in a therapeutic program (cell/gene therapy, genome editing, or RNA drugs).
• Ability to walk through results and show how evidence guided candidate selection and study design.
• Experience interpreting evidence relevant to modality, including safety and exposure signals.

Responsibilities

• Create case studies from cell therapy, gene therapy, or genetic medicine programs.
• Frame decisions using experimental results, balancing potency and safety considerations.
• Collaborate with scientists and engineers to evaluate AI agents’ approach to decisions and identify overlooked evidence.
• Write concise assessments explaining support for recommendations and what evidence could change conclusions.

Skills

MS/PhD or equivalent

Therapeutic program experience

AI research in science

Scientific writing

Education

MS/PhD in a relevant field

Job description

Scientist, Cell and Gene Therapy (AI Research)

San Francisco or remote

* Full-time (W2 position with benefits + equity)

* $140k-180k on-target earnings (base + performance bonus)

Our client is a team that researches and grades how AI performs when scientists ask it to recommend the next step in a drug program. The team is looking for a Scientist who has worked on a cell therapy, gene therapy, or genetic medicine drug program and can explain how the experimental results shaped what happened next.

What You Would Do:

• Create case studies drawn from cell therapy, gene therapy, or other genetic medicine programs. Examples might include choosing a cell source, comparing vector designs, or selecting an RNA therapeutic for further testing.
• Use experimental results to frame decisions scientists face in development, such as whether a potency advantage outweighs a safety concern or which experiment would resolve conflicting findings.
• Work with scientists and engineers to evaluate how AI agents approach those decisions. Identify evidence an agent overlooked, assumptions it made, and whether its proposed next step would answer the scientific question.
• Write concise assessments explaining which recommendations the data support, where uncertainty remains, and what evidence would change your judgment.

Your Background:

• You have an MS, PhD, or comparable professional experience, working directly on a therapeutic program involving cell therapies, viral vectors, genome editors, or RNA drugs such as ASOs, siRNAs, or mRNA.
• You’ve personally designed constructs, screened drug candidates, improved delivery, or planned studies for an IND. You can walk through a result that changed which candidate, dose, or experiment your team chose.
• You can interpret the evidence that matters for your modality, whether that’s editing specificity, tissue exposure, immune response, or a safety finding. Experience contributing to a nonclinical regulatory package is valuable.
• You are familiar with using AI agents for your research, and can explain in writing where a recommendation holds up, where the reasoning breaks down, and what evidence would change your view.