AI Biologist - Aging & Longevity

Latch builds rigorous scientific benchmarks (benchmarks.bio) 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 to join our Aging & Longevity team to help accelerate the discoveries AI can make in aging biology.

About the Role

You will use your scientific expertise to improve the ability of AI agents to reason like expert geroscientists. You will build tasks which evaluate aging-specific analysis capabilities and scientific taste. Your judgment will set the standard AI agents are evaluated against.

In this role, you will help accelerate research across the entire aging and longevity ecosystem.

You will work as part of a team of scientists and software engineers building benchmarks testing capabilities ranging from basic geroscience research to therapeutic discovery and development, including:

• Development, application, and interpretation of biomarkers of aging, such as proteomic and epigenetic clocks

• Design and analysis of experiments related to the Hallmarks of Aging, such as quantification of cellular senescence, identification of stem cell exhaustion, and measurement of genomic instability

• Integration and analysis of diverse data modalities, such as transcriptomics, proteomics, DNA methylation, functional measurements, health records, and imaging data

• Use of high-throughput screening data to discover and prioritize candidate anti-aging drug targets

Requirements

• Advanced degree (MS/PhD) in biology, bioinformatics, computational biology, or a related field

• Contribution to published research in aging biology or an adjacent field (cancer, epigenetics, immunology, etc.), such as a first-author paper, thesis, or independent project.

• Deep familiarity with AI coding tools

• An ability to convey your thoughts clearly and precisely; i.e., strong scientific writing skills

• High agency and initiative

• Demonstrated track record of using R or Python to analyze scientific data

• Deep computational or experimental experience:

• Computational: applying machine learning, data analysis, or statistics to -omics data; methods development; statistical genetics

• Experimental: hands-on wet-lab experience performing experiments and assays relevant to aging research (e.g., sequencing library prep, studies involving model organisms, senescence assays, flow cytometry, cell or organoid culture, in vivo intervention studies)

Strongly Preferred

• Industry experience in biotech, tech, or a similar field

• Multiple first-author publications

• Familiarity with frequently used repositories of scientific data, such as: the UK Biobank, TCGA, GEO, ENCODE, etc.

Compensation

$140K–$180K OTE (on-target earnings), with no ceiling.

• Your pay is your OTE times your weekly quota attainment. Hit quota, earn your OTE; double it, earn double. Example: $150K OTE at double quota = $300K.

• Your first 4 weeks (ramp) are paid at full OTE while you learn our workflows.

• You’re paid full OTE whenever quota can’t fairly apply: when a new project is starting, the platform goes down, or we pull you onto a special project.

Benefits & Employment

In the US: full-time W-2

• Guaranteed floor (“base salary”) set by your state, paid on the 15th and last day of every month

• Health, dental, vision: 100% covered for you, 50% for dependents

• 401(k) (no match)

• PTO: 15 days to start, more as you’re promoted

Outside the US: contractor

• Paid on performance. We want our team to have stability, so we pay 60% of your monthly OTE up front as an advance, balanced against your earnings in later paychecks.

• US benefits don’t apply.

Growth

Two tracks, based on output.

• Individual contributor: six levels, so up to five promotions, with OTE rising at each one.

• Management: after your first promotion, you can move into managing a pod or keep growing on the IC track.

Location & Work Authorization

• Location: remote or onsite at our Mission Bay office in San Francisco. Onsite is preferred: working side by side is how we share knowledge and keep our work rigorous. We have a global team, and remote teammates regularly visit the office.

• Work authorization: we sponsor H-1B (new and transfers), O-1, and TN, and support STEM OPT.

Culture @ Latch

We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’s always us against the problem, never each other. We’re opinionated but respectful of each other’s time, and we think through possible solutions before bringing a problem to anyone.

We use AI constantly, so we reward original expert judgment, not AI output passed off as your own. You’ll start on the bench that fits your expertise and can move across teams as you build a track record.

Outside of work: company outings most months, team off-sites, and a community that does cycling, soccer, figure skating, boxing, running, martial arts, music, books, and game nights.

Interview Process

1. Apply. If your profile matches, we’ll send you a take-home project.

2. Take-home project (HackerRank). We review it as soon as it arrives.

3. Technical interview with a Member of Technical Staff (pod lead).

4. Culture interview with our C-suite.

5. Offer.

6. Background check, once you accept.