AI Biologist - Microscopy

LatchBio • San Francisco, CA

12h • $120,000 - $180,000

About The Position

Latch builds scientific benchmarks for AI agents across biology and works with frontier labs and pharmaceutical companies to evaluate agents on real biological workflows. The AI Biologist will join the Microscopy team as the scientific authority on ground truth, evaluating whether AI agents can reason like expert microscopists and distinguish biological evidence from artifacts. The role involves working with software engineers and scientists to create benchmark tasks and datasets across cell biology, tissue, and disease.

The successful candidate will define expert reasoning for imaging questions and write defensible gold-standard answers; design realistic imaging-workflow scenarios; curate image datasets across multiple modalities; and build Python analysis pipelines, including deep-learning segmentation, that produce verifiable ground truth. They will also test agent performance, adjudicate ambiguous images, evaluate imaging choices, investigate reasoning failures, and score confidence with appropriate credit for uncertainty.

The role is a 1099 contract (or W-8BEN internationally) with no end date. Pay is guaranteed for the first four weeks during ramp-up, then paid per certified task. Most people in the position earn $120,000–$180,000 or more, with uncapped upside. The commitment is full-time on the employee’s own schedule; most of the team works 40 or more hours per week. The position can be remote, hybrid, or onsite in San Francisco, with onsite preferred. Onsite perks include catered lunch and dinner daily, a waterfront Mission Bay office, and monthly parking when available. Work authorization is limited to U.S. citizens, permanent residents, and OPT holders; STEM OPT extensions and sponsorship are not supported.

Requirements

• PhD in cell biology, bioimage analysis, pathology, or a related field, or an MD with pathology training.
• Senior, hands-on imaging experience, including examination of thousands of samples and knowledge of normal and abnormal appearances.
• Direct experience with image segmentation tools such as CellProfiler, Cellpose, StarDist, QuPath, ilastik, napari, or Fiji.
• Deep expertise in at least one of bioimage analysis, cell biology, or histopathology, and working fluency across the others.
• Strong command of experimental design, image quantification, and statistics.
• Daily use of Claude, Cursor, or similar AI agents, with the judgment to identify reasoning that is technically correct but scientifically unsound.
• Ability to overrule an AI agent when evidence requires it and openness to updating one’s judgment when shown to be wrong.
• Ability to calibrate confidence and communicate uncertainty rather than defaulting to binary conclusions.
• Must be a U.S. citizen, permanent resident, or OPT holder; STEM OPT extensions and sponsorship are not supported.

Nice To Haves

• Electron microscopy, pathology, or pharmacology experience, such as pharmacodynamic or drug-uptake imaging assays.
• Familiarity with public resources such as the Image Data Resource (IDR), BioImage Archive, Human Protein Atlas, Cell Painting Gallery, or TCGA whole-slide images.
• Leadership experience may support progression into senior roles.

Responsibilities

• Define expert reasoning for microscopy questions and write gold-standard answers with defensible rationales.
• Design realistic scenarios spanning sample preparation, staining, image acquisition, preprocessing, segmentation, quantification, and interpretation.
• Curate image datasets across immunofluorescence, confocal and live-cell imaging, electron microscopy, histology and histopathology, and high-content screening.
• Build Python analysis pipelines, including deep-learning segmentation, to produce verifiable ground truth.
• Partner with software engineers to turn scientific judgment into new workflows.
• Test whether agents distinguish true biological signal from artifacts such as bleed-through, uneven illumination, fixation damage, out-of-focus planes, and segmentation failure.
• Adjudicate ambiguous images, determine what the data supports and where experts may disagree, and identify additional evidence that could resolve uncertainty.
• Evaluate whether agents select appropriate imaging modalities, resolution, and units of analysis.
• Interrogate agent reasoning step by step and challenge conclusions that would not withstand expert review.
• Identify why agents fail, what an expert would do instead, and what evidence could change the conclusion.
• Score agent confidence, rewarding explicit uncertainty when images are ambiguous.

Benefits

• Catered lunch and dinner daily for onsite staff.
• Waterfront office in Mission Bay.
• Monthly parking when available.
• Company outings most months, team off-sites, and activities including a run club, cycling, boxing, ice skating, and soccer.
• Flexible scheduling; the role is on the worker’s own schedule.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree