AI Biologist - Genetic Medicine

Metric Bio; California; Remote; USD 150,000 - 220,000; Full time

Benefits offered by this job

Sign-on bonus $10,000

Fully remote option

Job summary

Metric Bio is seeking an AI Biologist – Genetic Medicines to join an innovative R&D team in evaluating AI applications in gene therapy, gene editing, and RNA therapeutics. The role focuses on developing datasets, case studies, and AI agent tasks spanning drug development from target validation to IND-enabling studies.

You will work with engineers and scientists to assess AI outputs, ensure scientific accuracy, and highlight risks or gaps in reasoning, while contributing to benchmarks for genetic

Qualifications

• Advanced degree (MS, PhD or PharmD) in Molecular Biology, Genetics, Gene Therapy or related biomedical discipline.
• At least three years' hands-on experience in gene therapy, gene editing or RNA therapeutics discovery or development.
• Direct experience in drug design, screening, or IND-enabling study design within a genetic medicine modality.
• Experience interpreting on-target and off-target editing data, biodistribution, immunogenicity and GLP toxicology.
• Familiarity with IND-enabling regulatory requirements and FDA/EMA nonclinical data packages.

Responsibilities

• Design realistic scientific case studies across target validation, drug design, screening and IND-enabling studies.
• Evaluate PK/PD data, immunogenicity findings and GLP toxicology across genetic medicine modalities.
• Reconstruct drug development decisions from multiple sources.
• Review and challenge AI-generated outputs for scientific accuracy.
• Identify weaknesses in AI reasoning where conclusions may be pharmacologically unsound.
• Assess AI confidence when interpreting incomplete or conflicting preclinical data.
• Support development of robust scientific benchmarks for genetic medicine research.

Skills

Scientific writing

AI tool assessment

Independent work

Problem solving

Initiative

Education

MS/PhD/PharmD in Molecular Biology or related

Job description

Location: San Francisco, USA or Fully Remote

Employment Type: Full-time

Department: Research & Development

Additional Incentive: $10,000 sign-on bonus for candidates who start within two weeks of signing.

About the Opportunity

We are seeking an experienced AI Biologist – Genetic Medicines to join an innovative team working at the forefront of artificial intelligence and biotechnology.

The organisation develops scientific benchmarks and evaluation frameworks for AI agents across biology, working with leading research laboratories and pharmaceutical organisations to assess AI capabilities in real-world biological workflows.

This role will focus on evaluating the application of artificial intelligence across gene therapy, gene editing and RNA therapeutics, helping to advance the development of genetic medicines.

The Role

You will contribute to the development of technical approaches for evaluating AI agent performance across the genetic medicines pipeline, from target validation and drug discovery through to clinical development.

Working alongside software engineers and scientific specialists, you will help develop datasets, case studies and AI agent tasks covering the full drug development process.

Key responsibilities will include:

• Designing realistic scientific case studies covering target validation, drug design, screening, chemistry optimisation, candidate selection and IND-enabling studies.
• Evaluating pharmacokinetic and pharmacodynamic (PK/PD) data, immunogenicity findings and GLP toxicology results across different genetic medicine modalities.
• Reconstructing drug development programme decisions using information from multiple scientific sources.
• Reviewing and challenging AI-generated outputs to ensure scientific accuracy and practical relevance.
• Identifying weaknesses in AI reasoning, particularly where conclusions may be theoretically correct but scientifically or pharmacologically unsound.
• Assessing AI confidence when interpreting incomplete, conflicting or uncertain preclinical data.
• Supporting the development of robust scientific benchmarks for genetic medicine research.

To be considered for this position, you will have:

• An advanced degree (MS, PhD or PharmD) in Molecular Biology, Genetics, Gene Therapy or a related biomedical discipline, or equivalent industry experience.
• At least three years' hands-on experience in gene therapy, gene editing or RNA therapeutics (ASO, siRNA or mRNA) discovery or development.
• Direct experience in drug design, drug screening, delivery optimisation or IND-enabling study design within at least one genetic medicine modality.
• Experience interpreting on-target and off-target editing data, biodistribution, immunogenicity and GLP toxicology to support dose selection and risk assessment.
• An understanding of potency, specificity and developability considerations across vectors, constructs or oligonucleotide candidates.
• Strong scientific writing skills, with the ability to produce clear, evidence-based recommendations and drug development rationale.
• Experience using AI agents and the ability to critically assess AI-generated scientific reasoning.
• The confidence to work with uncertainty, identify missing information and proactively highlight potential risks or gaps.A proactive approach, strong initiative and the ability to work independently.
• Familiarity with IND-enabling regulatory requirements and the nonclinical data packages expected by the FDA and EMA.

You will be joining a collaborative, ambitious and transparent working environment where scientific expertise, independent thinking and problem-solving are highly valued.

The organisation encourages open communication, shared responsibility and a solutions-focused approach.

AI tools are integrated into everyday working practices, with particular emphasis placed on original scientific judgement and expert insight rather than simply relying on AI-generated outputs.

There will also be opportunities to develop your expertise and move across different teams as your experience and contribution grow.

Team activities and social events include cycling, football, running, boxing, martial arts, music, book clubs and regular team gatherings.