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Neuralink

Software Engineer, Pathology and Digital Imaging

Austin, Texas, United StatesFrom $216kmidAdded 1 month ago

About this role

Neuralink is seeking a Software Engineer for their Pathology and Digital Imaging team, responsible for developing software that supports the analysis and tracking of tissue specimens in preclinical studies. The position emphasizes collaboration and rapid deployment, with a focus on building scalable tools for scientists in the field.

What you'll do

  • Manage the software stack for pathology and histology operations
  • Develop a tissue specimen tracking system
  • Create a high-performance image viewer for microscopy images
  • Build annotation tools for pathology findings
  • Implement ML annotation pipelines for large datasets
  • Collaborate closely with pathologists and neuroscientists

What they're looking for

  • Bachelor's degree in Computer Science or equivalent experience
  • Strong full-stack engineering skills (Ruby on Rails, React/TypeScript)
  • Experience in developing user-centered software
  • Strong collaboration and communication skills
  • Problem-solving and ownership mindset
  • Ability to navigate ambiguity

Benefits

  • Opportunity to impact the world through innovative technology
  • Growth potential for high-performing team members
  • Comprehensive medical, dental, and vision insurance
  • Paid holidays and commuter benefits
  • Provided meals
  • Equity compensation (RSUs)
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Neuralink

Neuralink develops brain-computer interface technology and neurosurgical robots to enable direct interaction between the brain and computing systems. The company is hiring engineers across clinical implementation, user interface design, manufacturing, and software development to support its pioneering medical devices and surgical systems.

View all jobs at Neuralink

Likely interview questions

  • Walk us through a full-stack project you've built end-to-end. How did you approach the frontend and backend, and what was the most challenging part?
  • Describe a time when you had to talk directly with users or customers to understand their problems. How did you translate their feedback into product decisions?