Sr Software Engineer Navigation

Job description

Job responsibilities

• Design and implement high-performance C++ data pipelines (shared-memory ring buffers, lock-free queues, time-synchronized capture) that feed live video, kinematics, and sensor streams into CV/ML algorithms on embedded…
• Develop and optimize registration and calibration algorithms, including point-cloud alignment, hand-eye calibration, and forward kinematics-based coordinate frame transformations to enable accurate surgical navigation
• Collaborate with ML engineers to integrate inference models (depth estimation, 3D reconstruction) into the real-time navigation stack, ensuring accuracy and latency budgets are met
• Partner with UI/graphics engineers to create navigation overlays, 3D visualizations, and augmented guidance within the embedded Qt/QML interface
• Build and maintain effective working relationships across software engineering, clinical engineering, design, human factors, and regulatory teams
• Own the medical device software lifecycle end-to-end for navigation components, including requirement definition, risk assessment, prototyping, development, verification, and release

Job requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field
• Minimum of 8 years of industry experience; or Master’s degree and 6 years of experience; or a PhD and 3 years of experience, with a proven track record of shipping production-quality C++ software to products
• Strong working knowledge of C++ (11/14/17+) including system-level programming, memory management, multi-threading, and performance optimization for real-time applications
• Experience designing or optimizing low-latency data pipelines (circular buffers, shared memory IPC, producer/consumer synchronization) on Linux
• Working knowledge of geometric computer vision fundamentals (camera calibration, registration, multi-view geometry, coordinate-frame transformations)
• Familiarity with ML inference frameworks (TensorRT, ONNX Runtime) and GPU-accelerated computing (CUDA)
• Experience with robotic kinematics, forward/inverse kinematics solvers, or SLAM
• Experience with 3D graphics frameworks (Qt3D, OpenGL, Vulkan, etc.)