Agile Programming Methodologies, Analysis Skills, Artificial Intelligence (AI), Computer Science, Data Sets, Digital Photography, Engineering, Histology, Image Viewer, JSON, Manufacturing, Microscopic Analysis, Microscopy, Necropsy, Pathology, Predictive Modeling, React.js, Ruby on Rails, Software Engineering, Team Player, Web Browsers
LOCATION
Austin, TX
POSTED
30+ days ago
Team Description:
The Pathology and Digital Imaging team enables the rigorous preclinical studies our devices go through before reaching a user. Testing is precise; analyzing tissue to understand exactly what happened at the cellular level. This team is crucial for proving safety, improving our device, and pushing science forward.
Histological analysis has shown that Neuralinks threads preserve 98% of neurons at the implant interface. The Pathology and Digital Imaging Team makes these kinds of analyses possible.
This is a small, tightly knit team, and youll work directly with pathologists, technicians, and neuroscientists. Youll watch them use your software, hear whats slow, see whats confusing, and ship fixes and features fast. The feedback loop is measured in hours, not sprints.
Job Description and Responsibilities:
As a Software Engineer on the Pathology and Digital Imaging Team, youll own the software stack that powers Neuralinks pathology and histology operations. This spans the full lifecycle - from the moment tissue is collected at necropsy, through processing, staining, and imaging.
Youll build the software that makes this analysis scalable: tracking thousands of tissue specimens from collection through microscopic analysis, giving scientists the tools to analyze billion-pixel images, and building AI tools to auto-analyze tissue response.
Projects you will work on:
Tissue specimen tracking systems that follow samples, organ blocks, and slides through every step of the histology workflow
A high-performance whole-slide image viewer that renders billion-pixel microscopy images in the browser
Annotation and analysis tools that let scientists draw regions of interest, score pathology findings, and compare serial sections with image alignment and overlay
ML annotation pipelines where model predictions are surfaced to scientists for validation, accelerating the analysis of large tissue datasets
Required Qualifications:
A bachelors degree in Computer Science or equivalent demonstrated work experience
Strong full-stack engineering skills. Our stack is Ruby on Rails and React/TypeScript, but we care more about your ability to learn and ship than your resume matching our package.json
Youve built software that real people use
You can talk to users, understand their problems, and translate that into well-built software. This role is deeply collaborative
You take ownership. When your software breaks on the floor, you fix it
Youre comfortable with ambiguity. Manufacturing at this scale hasnt been done before for this kind of device