Senior Software Engineer
Are you passionate about delivering excellence and making a real impact? Do you thrive on applying sharp analytical skills, innovative thinking, and technical expertise to meaningful challenges? If so, we invite you to explore an exciting opportunity with us.
VISIE is a dynamic medical device startup in Austin, Texas, pioneering a computer vision platform that redefines surgical navigation and robotics. Our technology integrates real-time, pinpoint-accurate 3D surface measurements into clinical workflows, enhancing how preoperative CT and MRI data are used during surgery for greater precision and decision-making.
Join our close-knit team of experts and help shape the future of the digital operating room, improving outcomes for millions of patients worldwide.
To apply, send your resume and cover letter to
What You Will Be Doing:
Real-Time Algorithm Optimization
Design, implement, and optimize algorithms for low-latency performance, focusing on parallel vs. serial execution trade-offs.
Leverage multi-threading, GPU acceleration (CUDA), or SIMD to reduce end-to-end processing times in live surgical environments.
Low-Latency Memory & DMA Collaboration
Minimize memory copies by employing zero-copy or shared-buffer strategies to reduce overhead in data-intensive workflows.
Work with embedded hardware engineers to integrate DMA-based data transfers, ensuring high-throughput, real-time data flow between devices and user-space applications.
Performance & Profiling
Profile system performance to identify bottlenecks (CPU, GPU, or memory) and apply targeted optimizations.
Collaborate with hardware/firmware teams to ensure cross-platform tuning, spanning embedded SoCs and host Linux systems.
Feature Ideation & Prototyping
Contribute to feature design and rapid prototyping, iterating on user feedback from surgeons and system integration engineers.
Ensure code quality and system responsiveness through regular refactoring and robust testing.
Verification & Validation
Develop unit tests, integration tests, and benchmarks to maintain reliability under real-world conditions.
Document code changes and participate in design reviews, upholding medical device quality standards (IEC 62304, ISO 13485).
Required Skills, Education, and Experience:
Advanced Degree: M.S. or Ph.D. in Computer Science, Engineering, Mathematics, Physics, or a related field (or equivalent industry experience).
Real-Time Programming: Demonstrated success in writing and optimizing code for real-time or near-real-time applications.
Parallel & Low-Latency Computing: Hands-on experience with multi-threading, GPU programming (CUDA/OpenCL), or SIMD to accelerate algorithms.
Memory & Data Transfer Optimization: Familiarity with zero-copy, DMA integration, and other techniques to reduce data movement overhead.
Proficient in C and Python: Skilled with memory management and performance tuning in both languages; experience with bindings (Pybind, Cython) is a plus.
Computer Vision & Image Processing: Background in image analysis, 2D/3D transformations, or point cloud processing.
Profiling & Debugging Tools: Strong command of performance profilers (e.g., NVIDIA Nsight, gprof, Valgrind) and concurrency debugging.
Source Control & Best Practices: Adept with Git, code review processes, and continuous integration (CI/CD).
Ways to Stand Out:
Medical Device Experience: Familiarity with regulated environments (ISO 60601, IEC 62304, etc.).
Advanced Parallelization: Expertise in advanced GPU optimization, distributed systems, or HPC frameworks for real-time performance.
Robotics & Controls: Knowledge of merging real-time algorithms with robotic motion planning and feedback loops.
Machine Learning: Experience using deep learning frameworks (TensorFlow/PyTorch) for segmentation, classification, or detection tasks.