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DeepHealth

AI-driven medical imaging and informatics platform

Engineering Manager - Mammography

Engineering LeadershipUpdated on Nov 13
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Ability to communicate status, risks, and trade-offs clearly to technical and non-technical audiences.
  • Ability to coordinate with platform, AI, and data teams on dependencies.
  • Strong grasp of the Mammo system and ability to participate in design and architecture reviews, challenge estimates, and unblock the team.

Responsibilities

  • Lead and mentor a team of 3 to 4 engineers and support their technical and professional growth.
  • Set clear goals, run regular one-on-one meetings and performance reviews, and give constructive feedback.
  • Recruit, onboard, and retain engineers.
  • Foster a culture of ownership, quality, and continuous improvement.
  • Own the Mammo release plan jointly with the product lead, including scope, sizing, milestones, and monthly release tracking.
  • Drive each release end to end through planning, development, verification, regulatory sign-off, deployment, and post-release follow-up.
  • Align the Mammo team's delivery practices, processes, and tools with Clinical AI standards.
  • Ensure test setups are ready so product can run functional validation on time.
  • Contribute to the three- and six-month roadmap rituals and keep delivery commitments predictable.
  • Work with QRC on regulatory impact assessments for every change.
  • Coordinate with platform, AI, and data teams on dependencies.
  • Participate in design and architecture reviews, challenge estimates, and unblock the team.
  • Maintain a strong grasp of the system without writing production code day to day.

About the Company

DeepHealth

AI-driven medical imaging and informatics platform

DeepHealth provides AI-powered medical imaging and health informatics solutions that help radiologists analyze X-rays, CTs, and MRIs by automating parts of image interpretation, highlighting areas of concern, and delivering quantitative insights. It works by integrating AI into radiology workflows via cloud-based software, enabling automated image analysis, scoring, and reporting within enterprise imaging systems. The company differentiates itself through its integration with RadNet and strategic acquisitions of iCAD and CIMAR UK, expanding breast imaging capabilities, interoperability, and the scale of its deployments. Its goal is to accelerate the adoption of AI in real-world healthcare, improve diagnostic accuracy and consistency, and streamline imaging workflows across hospitals and health systems.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Cambridge, MA
Founded
2017

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