Design and validate reliable remote connectivity for the ARIES program from an on-site role in Newton, MA. Siemens Healthineers is building communication and hosting infrastructure that supports long-distance operation across distributed robotic and computational systems, spanning networking, middleware, containerized and virtualized environments, and GPU-enabled pipelines.
What you’ll be doing
You will partner with software engineers, system architects, networking specialists, and other contributors to define remote connectivity requirements and integration concepts. Your work will focus on designing, implementing, and improving infrastructure that enables dependable communication across wide area networks.
- 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 over wide area networks.
- Develop reusable software infrastructure to host and orchestrate containerized or virtualized software environments across computational platforms.
- Extend existing remote connectivity protocols to exchange additional system data, status information, and operational metadata.
- Implement components that monitor and expose the liveliness, quality, and health of remote connectivity links so external systems can observe performance and communication status.
- 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.
What you bring
- 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 with 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 infrastructure for Docker, Kubernetes, virtual machines, or comparable containerized/virtualized 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 for real-time data or image processing.
- Experience building monitoring, diagnostics, liveliness reporting, or software interfaces that expose communication quality metrics to external systems or observability tools.
- Experience creating test cases and contributing to continuous integration, automated testing, validation pipelines, and technical documentation.
- Familiarity using AI-assisted coding technologies to support development workflows including code review, documentation, testing, and debugging.
Compensation & benefits
Salary range: USD 118,300 - 162,668 per year.
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k) retirement plan
- Life insurance
- Long-term and short-term disability insurance
- Paid parking/public transportation
- Paid time off
- Paid sick and safe time
Preferred experience
- 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.
Education
Preferred: Master’s degree or specialized training in robotics, distributed systems, real-time systems, or medical device software development.
Required (stated): Bachelor’s degree in Computer science, Software Engineering, Robotics, Electrical Engineering, Biomedical Engineering, o
