Software Developer Computer Vision/ Intelligence Logic

Siemens Healthineers

17d•$118,300 - $162,668

About The Position

Lead the Intelligence Logic team responsible for the next generation of endovascular robotic interventions. The team’s work spans real-time image analytics for device navigation and computer vision, as well as procedural workflow orchestration that models, predicts, and automates neuroendovascular procedures. The role sets technical direction across computer vision/AI imaging and workflow orchestration, and coordinates development of integrated image analytics, sensor fusion/localization, and workflow engines for use in the interventional suite, in close alignment with development teams in Germany. Oversee development and evaluation of deep learning approaches for real-time image analysis—including segmentation, registration, object detection, and tracking—and state machines and digital representations of neurovascular procedures. Work with multimodal data, including X-ray fluoroscopy, digital subtraction angiography, cone-beam computed tomography, robotic data, and endovascular device shape sensing. Collaborate with computer vision, robotics, clinical, and hardware experts to support safe workflow orchestration, including failure detection and uncertainty estimation. Manage team priorities, sprint planning, delivery milestones, and blockers while ensuring DevOps and MLOps practices across the software and machine-learning lifecycle. The position is in an interdisciplinary, regulated medical-device environment. Siemens Healthineers describes itself as a global medical technology company with more than 72,000 employees in more than 70 countries. The stated base pay range is $118,300–$162,668. The company lists medical, dental, and vision insurance; a 401(k) retirement plan; life and disability insurance; paid parking or public transportation; paid time off; and paid sick and safe time, subject to eligibility requirements.

Requirements

Master’s degree in Biomedical Engineering, Computer Science, Artificial Intelligence, Robotics, or a related field.
At least 6 years of experience.
Prior experience leading or mentoring engineers and/or software developers, such as in a technical lead, team lead, or similar people-management capacity in a software or R&D organization.
Strong background in computer vision and medical image analysis, including segmentation, registration, and object detection and tracking.
In-depth understanding of state-of-the-art deep-learning methods.
Strong background in robotics concepts, including state estimation and sensor fusion.
Working knowledge of control theory concepts such as model predictive control.
Experience developing machine-learning models with modern frameworks such as PyTorch and applying MLOps approaches across the model lifecycle.
Experience programming with Python and C++/CUDA.
Software engineering experience following DevOps best practices.
Very good written and spoken English.
Strong leadership, coaching, and communication skills, including the ability to motivate a technically diverse team and align it around shared goals.
Organizational skills, communication abilities, initiative, and curiosity to learn.

Nice To Haves

PhD degree; highly preferred.
Scientific publications in relevant top-tier journals or venues such as IEEE TMI, CVPR, ICCV/ECCV, MICCAI, or comparable venues.

Responsibilities

Lead and mentor software developers in computer vision/AI imaging and workflow orchestration, setting technical direction and aligning the two disciplines.
Coordinate and shape the technical roadmap for integrating AI-driven image analytics, sensor fusion/localization, and workflow engines that coordinate imaging and robotics in the interventional suite.
Work in close alignment with and support development teams in Germany.
Oversee development and evaluation of deep-learning methods for real-time image analysis, including segmentation, registration, object detection, and tracking.
Oversee development of state machines and digital representations of neurovascular procedures.
Collaborate with computer vision, robotics, clinical, and hardware experts to support safe clinical workflow orchestration, including failure detection and uncertainty estimation.
Manage team priorities, sprint planning, and delivery milestones; remove blockers.
Ensure the team follows DevOps and MLOps best practices throughout the software and machine-learning model lifecycle.
Work with multimodal data including X-ray fluoroscopy, digital subtraction angiography, cone-beam computed tomography, robotic data, and endovascular device shape sensing.
Collaborate in an interdisciplinary, regulated medical-device environment.