Intuitive Autonomy

Intuitive Autonomy

Clinical Applications Engineer

Boston, MA, United States · Mid · Contract

Sponsorship not specifiedDetected 5 days ago
AccessibilityLogisticsPatient CareCommunicationCollaboration

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • Nearly 30 years later, that question still fuels everything we do at Intuitive.
  • As a global leader in robotic-assisted surgery and minimally invasive care, our technologies-like the da Vinci surgical system and Ion -have transformed how care is delivered for millions of patients worldwide.

Responsibilities

  • Provide procedural support to new robotic system sites to promote safety and effective
  • Collaborate with global Clinical Applications Engineering and Endoluminal Sales to support new
  • Identify key areas of concern for clinical users for procedure adoption and collaborate with
  • Drive collaboration and maintain consistent, open lines of communication across the assigned
  • Collaborate with peers and development engineering partners to develop and share best
  • Problem solver who can maintain composure and think critically in high pressure environments

Requirements

  • Experience navigating hospitals and supporting procedures required

Skills

  • It started with a simple idea: what if surgery could be less invasive and recovery less painful?

Benefits

  • A minimum of 2 years of technical or clinical experience in healthcare
  • Self-starter who performs well with autonomy and can be flexible in a dynamic work

Company info

  • If you require assistance or an accommodation during any part of the application or interview process, please contact People Services at HRHelpNow@intusurg.com.

Equal opportunity

  • Intuitive is an Equal Opportunity Employer.
  • Accommodation & Accessibility Notice:

This listing is sourced directly from Intuitive Autonomy's careers page and normalized into a canonical job model.