AI Biologist- Genetic Medicines

Metric Bio; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Metric Bio, in collaboration with LatchBio, seeks an AI Biologist - Genetic Medicines to advance benchmarking of AI agents in gene therapy, gene editing, and RNA therapeutics. You will help build datasets and test agent reasoning across end-to-end genetic medicine pipelines.

Join a team of scientists and engineers shaping real-world preclinical workflows and evaluating model outputs for scientific rigor and practical defensibility.

Qualifications

• Advanced degree in molecular biology, genetics, gene therapy, or related biomedical field.
• 3+ years hands-on experience in gene therapy, gene editing, or RNA therapeutics discovery or development.
• Experience interpreting on-/off-target editing data, biodistribution, immunogenicity, and GLP toxicology.
• Familiarity with IND-enabling regulatory requirements and FDA/EMA expectations is a plus.
• Strong scientific writing skills with evidence-supported rationale for drug development decisions.

Responsibilities

• Contribute to evaluating agent performance across genetic medicines pipelines, including gene therapy, editing, and RNA therapeutics.
• Build datasets and AI agent tasks across end-to-end genetic medicine modalities.
• Design program case studies spanning target validation, screening, and IND-enabling studies.
• Evaluate PK/PD, immunogenicity, and GLP toxicology findings across modalities and stages.
• Review and stress-test agent outputs for scientific soundness and defensibility in program reviews.

Skills

Gene therapy experience

Data interpretation of editing data

Scientific writing

AI agent proficiency

Uncertainty tolerance

Education

MS/PhD/PharmD in molecular biology or related field

Job description

Metric Bio are working exclusively alongside the industry leading LatchBio on the search for their next group of AI Biologists in Medical Countermeasures.

This role is remote and can be done from anywhere in the World.

Latch create rigorous scientific benchmarks in the Biology space for AI Agents alongside Pharma and Frontier Labs to measure whether agents can handle the real world Biological Workflows.

About the Role

You will contribute to our technical approach for evaluating agent performance at reasoning across the genetic medicines pipeline – gene therapy, gene editing, and RNA therapeutics from target validation and drug discovery to clinical development.

You will work as part of a team of software engineers and scientists building datasets and AI agent tasks across the end-to-end genetic medicines pipeline, including:

• Designing realistic program case studies spanning target validation, drug design and screening, chemistry optimization, candidate nomination, and IND-enabling studies across genetic medicine modalities
• Evaluating PK/PD, immunogenicity, and GLP toxicology findings across modalities and development stages
• Reconstructing program go/no-go decisions from multi-source data
• Reviewing and stress-testing agent outputs for scientific soundness, catching reasoning that is textbook-correct but not defensible in a program review
• Calibrating AI agent confidence on preclinical data with incomplete or conflicting signals, rather than forcing a binary call

AI Biologics - Genetic Medicines

Latch builds rigorous scientific benchmarks for AI agents across biology. We work with frontier labs and pharma to measure whether agents can handle real biological workflows: the messy, multi-layer reasoning that matters in the field.

We’re seeking an AI Biologist - Genetic Medicines to join our team working at the frontier of what artificial intelligence can achieve in gene therapy, gene editing, and RNA therapeutics development.

About the Role

You will contribute to our technical approach for evaluating agent performance at reasoning across the genetic medicines pipeline – gene therapy, gene editing, and RNA therapeutics from target validation and drug discovery to clinical development.

You will work as part of a team of software engineers and scientists building datasets and AI agent tasks across the end-to-end genetic medicines pipeline, including:

• Designing realistic program case studies spanning target validation, drug design and screening, chemistry optimization, candidate nomination, and IND-enabling studies across genetic medicine modalities
• Evaluating PK/PD, immunogenicity, and GLP toxicology findings across modalities and development stages
• Reconstructing program go/no-go decisions from multi-source data
• Reviewing and stress-testing agent outputs for scientific soundness, catching reasoning that is textbook-correct but not defensible in a program review
• Calibrating AI agent confidence on preclinical data with incomplete or conflicting signals, rather than forcing a binary call

Requirements

• Advanced degree (MS/PhD/PharmD) in molecular biology, genetics, gene therapy, or a related biomedical field, or equivalent industry experience
• 3+ years of hands-on experience in gene therapy, gene editing, or RNA therapeutics (ASO/siRNA/mRNA) discovery or development
• Direct experience with drug design, drug screening, delivery optimization, or IND-enabling study design in at least one genetic medicine modality
• Experience interpreting on-/off-target editing data, biodistribution, immunogenicity, and GLP toxicology to inform dose selection and risk assessment
• Familiarity with IND-enabling regulatory requirements and the nonclinical data package expected by FDA/EMA is a plus
• Experience evaluating potency, specificity, and developability trade-offs across vector, construct, or oligonucleotide candidates
• Strong scientific writing skills, able to produce clear, evidence-supported rationale for a drug development decision
• Proficiency in AI agent use, with the judgment to identify where model reasoning is technically correct but pharmacologically or practically unsound
• Comfort operating in uncertainty, and proactively flagging gaps in data or instructions