Omnisource Technologies was founded in 2007 on the belief that great teams can change the world. Today, we partner with ambitious startups and global enterprises to solve complex, high-impact product and engineering challenges. Our work is driven by a commitment to product quality, engineering excellence, and user experience.

Job Summary

We’re looking for a Medical Device Software Engineer to help bring the R2 platform from prototype to clinical deployment. You’ll work closely with hardware engineers to build software for a next-generation imaging system running on NVIDIA Jetson hardware and the Holoscan SDK.

The platform integrates multimodal cameras (RGB, SWIR, thermal, and depth) with real-time image processing and AI to give clinicians unprecedented insight into wound pathology. In this role, you’ll design high-performance imaging pipelines, develop AI-driven analysis tools, and help create a clear, intuitive clinical interface—while ensuring the software meets IEC 62304 standards for FDA Class II medical devices.

Core Responsibilities

• Design and implement real-time imaging software that captures, synchronizes, and processes data from multiple camera modalities (RGB, SWIR, thermal, ToF) to support precise wound assessment
• Develop AI/ML pipelines for wound analysis, including segmentation, inflammation assessment, moisture/exudate detection, tissue oxygenation mapping, and healing progression
• Build and maintain a clinician-facing dashboard with multimodal visualizations, trend analysis, and AI-generated insights
• Optimize performance for embedded deployment on NVIDIA Jetson AGX Orin, ensuring low-latency, reliable real-time operation

Integration & Compliance

• Integrate software with custom hardware including multi-camera synchronization, calibration routines, LED illumination control, and network timing
• Collaborate closely with hardware and systems engineers to align software with evolving platform requirements and support future scalability
• Develop software in accordance with IEC 62304 and FDA Class II requirements
• Contribute to design documentation, risk analysis, and verification/validation activities required for regulatory clearance

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Biomedical Engineering, or a related field
• 3+ years of experience developing embedded or systems-level software
• Strong experience with real-time image processing and computer vision
• Proficiency in Python and C++ for performance-critical systems
• Experience deploying software on embedded Linux platforms (NVIDIA Jetson preferred)
• Familiarity with NVIDIA Holoscan SDK or similar real-time sensor fusion / streaming frameworks
• Familiarity with medical device software development practices and regulatory standards (IEC 62304, FDA Class II)
• Strong documentation and communication skills, especially in regulated environments

Technical Strengths (one or more of the following)

• Experience with NVIDIA Jetson, CUDA, TensorRT, or similar accelerated computing platforms
• Experience with multimodal imaging systems (RGB, thermal, SWIR, depth)
• Hands-on work with AI/ML models for medical or scientific imaging
• Experience with camera SDKs and multi-camera synchronization
• Knowledge of calibration techniques for imaging systems

Nice-to-Have

• Experience building clinician-facing dashboards using Qt, Electron, or modern web frameworks
• Comfort working with hardware prototypes, networking (10GigE), and programmable illumination systems
• Background in wound care, dermatology, or clinical imaging
• Experience supporting or leading FDA clearance for a medical device
• Certification in medical software development (AAMI TIR45 or equivalent)

Reasons to work with us

• Work on a product with real, measurable impact on patient care
• Be part of a small, highly skilled team solving genuinely hard problems
• Competitive compensation and flexible working arrangements
• Direct collaboration with hardware and clinical experts
• Ownership, autonomy, and the ability to shape a product from early-stage to clinical deployment
• Open, transparent communication and a strong engineering culture