Software Engineer, Aidence

Clinical AI Devices

€60-80k

AWS

Docker

Kubernetes

GCP

Java

SpringBoot

Senior and Expert level

Amsterdam

Paris

Remote from France, Netherlands

More information about location

AI-powered clinical applications for the lung cancer pathway

Be an early applicant

AI-powered clinical applications for the lung cancer pathway

1-20 employees

HealthcareB2BArtificial IntelligenceMachine LearningSaaSMedTech

Be an early applicant

€60-80k

AWS

Docker

Kubernetes

GCP

Java

SpringBoot

Senior and Expert level

Amsterdam

Paris

Remote from France, Netherlands

More information about location

1-20 employees

HealthcareB2BArtificial IntelligenceMachine LearningSaaSMedTech

Company mission

To provide AI that empowers healthcare and pharmaceutical professionals to deliver faster, more precise diagnostics and treatments.

Job

Company

Role

Who you are

Bachelor's or Master’s Degree in a related field such as computer science, biomedical engineering or similar (required)
Experience (required): at least 5 years of experience in a similar or related relevant role
At least 5 years of experience working with Java, with proficiency in Spring Boot (required)
Fluent in English (required)
Accustomed to CI/CD practice (required)
Familiar with test-driven development and testing frameworks like JUnit (required)
Experience working with docker, cloud platforms such as GCP or AWS, and Kubernetes (required)
Experience working with Agentic Coding tools like Claude and Cursor (preferred)
Experience working with microservices and distributed systems (preferred)
Experience in the MedTech field, e.g. working with DICOM data, AI algorithms, and clinical workflows (preferred)
Strong analytical mindset
Not afraid of working inside a strong regulatory framework and disciplined about testing needs
Ability to make well-reasoned trade-offs between velocity and quality, understanding when to work for higher quality and when to optimize for time-to-market
You collaborate openly, support your colleagues, and contribute to shared success

What the job involves

In the Clinical AI Devices team, the Software Engineer is primarily responsible for building and maintaining software in the Clinical AI domain, from wrapping deep learning models into containerized medical devices, to integration with other systems
This work spans all of the company's medical devices, across the main radiology modalities: X-Ray, CT, MRI, and Mammography
The focus of the current role is at the interface between product logic and the underlying serving platform, ensuring that requests are correctly validated, routed, and that results are properly assembled and returned
Participate in the software development process: design, refine, and develop new features, and maintain existing ones
Write code, review teammates' code, and contribute to the testing framework through automated and manual tests. Work with the team lead and product manager to refine requirements
Own features and projects end-to-end, from refinement to production. Flag risks and bugs by keeping the radiologist's workflow in mind. Support service and delivery teams with production issues
Ensure compliance with Quality and Regulatory requirements throughout the development cycle, including technical documentation (e.g. implementation specs), cybersecurity processes, and risk analysis
Collaborate with the team on strategic recommendations and improvements to technology and business
PLEASE NOTE: This is not an exhaustive list of all duties, responsibilities and requirements of the position described above. Other functions may be assigned, and management retains the right to add or change duties at any time

Our take

The medical technology market is expected to continue its growth due to innovative technological developments, the increasing pace of population ageing, chronic diseases, and trust in medical devices. Alongside this, advancements in AI and robotic solutions, cloud-based software and healthcare apps, are likely to boost industry growth in the future.

Radiologists agree that AI is necessary to compensate for the increase in medical images they need to assess. Without AI, the demand for scans would outgrow the human ability to review them timely and accurately. Aidence provides an AI solution for lung nodule detection and management, which helps improve lung cancer prognosis by detecting, measuring, classifying and tracking the growth of pulmonary nodules on patients' chest CT scans.

Aidence was acquired by US radiology firm RadNet in 2022. Its future goals include expanding its products to detect larger masses on chest CTs and using the data collected from scans to provide further insights into the effectiveness of lung cancer treatments.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 3 rounds)

Mar 2020

$2m

GRANT

Feb 2019

$11.3m

SERIES A

Total funding: $15.8m

Company HQ

De Weteringschans, Amsterdam, Netherlands

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