Staff Software Engineer, Neuronavigation and Autonomy

Magnus Medical•Burlingame, CA

2d•$170,000 - $220,000•Onsite

About The Position

Magnus Medical is seeking a Staff Software Engineer to be the technical owner of their real-time neuronavigation and autonomous treatment delivery system. This system tracks the patient's head live, localizes the treatment coil in the patient's imaging space, and guides a robotic arm to place and hold the coil on target during treatment sessions. The role involves working at the intersection of computer vision, real-time systems, and robotics, and is accountable for the system through to release. The scope includes live tracking, coil localization, robotic integration, automated coil placement, automated motor threshold determination, and the safety architecture for autonomous operation. The engineer will also be responsible for bench testing to prove clinical accuracy under FDA design controls. This is a senior individual contributor role requiring depth in one area and systems-level thinking across others, with the ability to judge when results are sufficient for patient treatment. The position is based onsite in Burlingame, CA.

Requirements

MSc. degree in computer science, engineering, physics, applied mathematics, or a related technical field, or equivalent practical experience
Expert-level modern C++ with 6+ years delivering production real-time systems: multi-threaded and concurrent design, deterministic low-latency execution, memory and cache-aware optimization, and profiling under hard timing constraints
Proficiency in Python for algorithm prototyping, data analysis, and tooling
Depth in at least one of the following, with the appetite to build competence in the others: geometric computer vision and 3D perception; numerical methods for spatial estimation and sensor fusion; robotics, including kinematics and real-time control; machine learning for perception
Working knowledge of camera calibration, registration, multi-view geometry, rigid-body transforms, and coordinate-frame reasoning
Experience building deterministic data flow over asynchronous sensor streams on Linux, including buffering strategies and time synchronization across devices
Experience with closed-loop or autonomous systems, including state machines, degraded modes, and safety-aware design
A measurement-driven approach to accuracy and robustness, including designing and running the bench tests that prove a system meets its requirements
Demonstrated ownership of a complex subsystem from algorithm through released product, including evolving a substantial codebase you did not write
Systems-level thinking, with the ability to set technical direction independently and work across engineering, clinical, quality, and regulatory teams

Nice To Haves

Software development in a regulated medical device environment: IEC 62304, ISO 14971, design controls, and documentation that has supported an FDA submission or audit
Familiarity, knowledge and/or experience with 21 CFR 820, Quality Management System Regulation, preferred/desired
Surgical navigation, robotic surgery, or another image-guided or safety-critical autonomous system, including patient-to-image registration
Robot integration: hand-eye calibration, forward and inverse kinematics, impedance or force control, vendor real-time control APIs or ROS, and functional safety
Cameras and depth sensors (stereo, structured light, time-of-flight), including vendor SDKs and driver-level integration
Closed-loop physiological control or biosignal processing, such as EMG, evoked potentials, or adaptive stimulation
GPU-accelerated computing such as CUDA, and ML inference frameworks such as TensorRT or ONNX Runtime
Familiarity with MRI-based anatomical models and coordinate spaces, and with TMS or neuromodulation

Responsibilities

Own the real-time neuro-navigation and autonomy stack end to end: architecture, algorithms, performance, and correctness
Develop, optimize, and validate live head tracking and coil localization, treating accuracy, robustness, and latency as one problem: computer vision, registration, sensor fusion, and filtering against system-level accuracy requirements
Design and optimize the C++ runtime connecting live sensor and robot data to CV and ML inference: low-latency data flow, concurrency, and GPU acceleration within a fixed latency budget
Own integration with the robotic arm: real-time control interfaces, hand-eye and tool-tip calibration, coordinate frames across imaging, tracking, robot, and patient, and motion constraints for work near a patient
Build the closed-loop autonomy that delivers treatment: automated coil placement on target and continuous motion compensation and drift correction through a session
Develop automated motor threshold determination: closed-loop control of stimulation intensity, detection of the motor response, and adaptive threshold estimation
Design the safety architecture for a system operating autonomously on a patient: interlocks, workspace and force limits, clinician override, and defined behavior on tracking loss or other degraded conditions
Apply machine learning to perception where it outperforms classical methods: semantic segmentation, landmark detection, and instrument detection, validated to clinical standards
Own sensor integration across cameras, depth sensors, and optical trackers: calibration, time synchronization, and error characterization
Own the accuracy and robustness test strategy and prove the system meets it: bench, phantom, and system-level accuracy testing with the fixtures and ground truth it depends on; identify failure modes; author the protocols and reports supporting design verification and FDA submissions
Own the medical device software lifecycle for these components: requirement definition, risk assessment, design documentation, and release
Own the interfaces to the upstream imaging pipeline that supplies anatomical models and targets, and to the clinical software that presents guidance
Set technical direction, mentor engineers, and work across clinical, scientific, quality, and regulatory teams
Work onsite in Burlingame, CA, with regular hands-on time on sensors, robot, and bench test fixtures