Software Engineer

Siemens Healthineers

3d•$114,920 - $158,015

About The Position

The Software Engineer will be responsible for designing, integrating, and validating remote connectivity communication and hosting infrastructure for the ARIES (Autonomous Robotics & Imaging Ecosystem for Stroke) program. Working closely with software engineers, system architects, networking specialists, and other engineering contributors, this role will support the integration of long-distance communication capabilities across distributed robotic and computational systems. The position requires hands-on experience with networking, middleware configuration, containerized or virtualized environments, GPU-enabled software frameworks, and robust software engineering practices to enable reliable remote operation, monitoring, testing, and scalability.

Requirements

Minimum 3 years of professional software engineering experience with C++ and Python, preferably in robotics, distributed systems, networking, embedded systems, or comparable cyber-physical environments.
Hands-on experience designing, integrating, or troubleshooting remote connectivity infrastructure such as VPNs, VLANs, routing configurations, firewalls, and secure network communication.
Experience with DDS or comparable middleware, including configuration and tuning of quality of service parameters for reliable distributed communication.
Experience developing reusable software infrastructure for containerized or virtualized environments, including Docker, Kubernetes, virtual machines, or comparable technologies.
Experience with image or video streaming across networks using frameworks such as GStreamer, NVIDIA Holoscan, ROS, DDS, or comparable technologies.
Practical experience with GPU-enabled software environments, acceleration frameworks, and computational platforms used for real-time data or image processing.
Experience developing monitoring, diagnostics, liveliness reporting, or software interfaces that expose communication quality metrics to external applications or observability tools.
Experience creating test cases and contributing to continuous integration, automated testing, validation pipelines, and technical documentation.
Familiarity with using AI-assisted coding technologies to support software development, code review, documentation, testing, or debugging workflows.

Nice To Haves

Prior experience developing remote connectivity, teleoperation, distributed robotics, medical robotic platforms, autonomous systems, or image-guided therapy systems.
Experience with ROS, NVIDIA Holoscan, GStreamer, DDS implementations, or comparable middleware and streaming frameworks.
Experience integrating software with real hardware, sensors, actuators, GPUs, edge computers, cloud resources, or other computational platforms.
Experience with medical device development, regulated product development, or safety-critical software is a plus.
Willingness to learn new technologies, adapt to evolving technical needs, and contribute in a fast-moving research and development environment.

Responsibilities

Collaborate with software engineers, system architects, networking specialists, and other contributors to define remote connectivity requirements and integration concepts.
Design and integrate remote connectivity infrastructure, including VPNs, VLANs, routing concepts, and secure network configurations for distributed systems.
Configure and tune quality of service parameters for DDS or comparable middleware to support reliable long-distance communication across wide area networks.
Develop reusable software infrastructure for hosting and orchestrating containerized or virtualized software environments across computational platforms.
Extend existing remote connectivity protocols to exchange additional system data, status information, and operational metadata.
Implement software components that monitor, report, and expose the liveliness, quality, and health of remote connectivity links so external systems can observe communication status and performance.
Enable image and video stream transmission across wide area networks using appropriate streaming frameworks, middleware, and GPU-enabled processing pipelines.
Support continuous testing, automation, documentation, code reviews, troubleshooting, and ongoing improvement of the remote connectivity software infrastructure.