AI Biologist - Microscopy
LatchBio is hiring an AI Biologist - Microscopy for a remote role open to applicants in United States. It pays $120k-$180k a year and Level rates it ; you can apply on LatchBio.
Level's read on this job
- On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions Claude, Cursor and Python among its tools and skills.
- LatchBio has 22 other open roles on Level.
- Posted within the past week.
AI in this role
Serve as the scientific authority on microscopy to build tasks and datasets evaluating AI agent reasoning in biological imaging.
AI Biologist - Microscopy
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 Microscopy team, pushing what AI can achieve in biological imaging.
About the Role. You will be the scientific authority on ground truth, testing whether agents can reason like an expert microscopist. AI agents today struggle to interrogate raw images, separate real biology from artifacts in acquisition, staining, and segmentation, and reach conclusions an expert would stand behind. Experts themselves disagree on roughly 1 in 6 images, so knowing where the evidence ends is part of the work. You will work with software engineers and scientists to build the tasks and datasets behind our benchmarks across cell biology, tissue, and disease. Your judgment will set the standard agent outputs are held to, including:
Build the task
Define what expert reasoning looks like for an imaging question, and write gold-standard answers with the rationale an experienced microscopist or pathologist would defend
Design realistic scenarios across the imaging workflow: sample prep, staining, acquisition, preprocessing, segmentation, quantification, and interpretation
Curate image datasets across modalities: immunofluorescence, confocal and live-cell, electron microscopy, histology and histopathology, and high-content screening
Build analysis pipelines in Python, including deep-learning segmentation, that produce verifiable ground truth
Partner with software engineers to turn your judgment into new workflows
Set the hard calls
Test whether agents distinguish true signal from artifact, such as bleed-through, uneven illumination, fixation damage, out-of-focus planes, or segmentation failure
Adjudicate ambiguous images: decide what the data supports, where reasonable experts would disagree, and which additional stain, image, or experiment would settle the call
Test whether agents choose the right imaging modality, resolution, and unit of analysis for the question
Judge the agent
Interrogate agent reasoning step by step, and challenge conclusions that sound right but would not survive pathologist review or lab meeting
Pinpoint where agents go wrong: why a step fails, what an expert would do instead, and what evidence would change the call
Score agent confidence, rewarding explicit uncertainty over overconfident calls on ambiguous images
Requirements
PhD in cell biology, bioimage analysis, pathology, or a related field; or an MD with pathology training
Senior, hands-on imaging experience: you have looked at thousands of samples and know what normal and abnormal look like
Direct experience with image segmentation tools such as CellProfiler, Cellpose, StarDist, QuPath, ilastik, napari, or Fiji
Deep expertise in at least one area (bioimage analysis, cell biology, or histopathology) and working fluency across the others
Strong command of experimental design, image quantification, and statistics
AI-ready from day one: daily use of Claude, Cursor, or similar agents, with the judgment to spot where model reasoning is technically correct but scientifically unsound
Confidence to overrule an AI agent when the evidence demands it, and the openness to update when shown wrong
Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary calls
Bonus: electron microscopy, pathology, or pharmacology experience (e.g., pharmacodynamic or drug-uptake imaging assays)
Bonus: familiarity with public resources such as the Image Data Resource (IDR), BioImage Archive, Human Protein Atlas, Cell Painting Gallery, or TCGA whole-slide images
Culture. We practice radical transparency: you’ll know how the company is doing, what’s working, and what isn’t. It’ll always be us against the problem, never each other. We’re opinionated but respectful, and we bring solutions with our problems. You decide how you work; we judge the output. We use AI constantly, so what we reward is 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. People who do well here and bring leadership experience can move quickly into senior roles. Outside of work, we have company outings most months, team off-sites, a Latch run club, cycling, boxing, ice skating, and soccer. Feel free to add to the list.
Compensation & Logistics
Contract: 1099 (or W-8BEN internationally), no end date
Pay: guaranteed for weeks 1-4 while you ramp, then paid per certified task. Most people in this position earn $120K–$180K+ (uncapped upside); certify twice the tasks/week, earn twice the pay that week.
Commitment: full-time, on your own schedule. Most of the team works 40+ hours a week.
Meetings: a few pod check-ins a week. The rest of your time is yours.
Location: remote (anywhere), hybrid, or onsite in SF. We prefer onsite.
Onsite perks: catered lunch and dinner daily, a waterfront office in Mission Bay, and monthly parking when available
Work authorization: US citizens, permanent residents, and OPT holders. We can’t support STEM OPT extensions or sponsorship.
Interview Process
We move fast: about 2–3 weeks from your first call, to offer.
Intro Screen - Latch Talent Team
Take-Home Project - HackerRank
Technical Interview - Member of Technical Staff
Culture Interview - C-Suite
Offer
How we rate this
AI Biologist - Microscopy at LatchBio rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where microscopy was part of your work. What did you do?
- Tell me about a project where pathology was part of your work. What did you do?
- Tell me about a project where image analysis was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Microscopy, Pathology, Image Analysis, and Deep learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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