Machine Learning Engineer

Job Description Kodiak Sciences (Nasdaq: KOD) is advancing vision science by integrating retinal biology, optics, artificial intelligence, medical imaging, and next-generation wearable technologies. Our VETi - Visual Engagement Technology and Imager - platform is an AI-enabled wearable system combining advanced LiDAR, Optical Coherence Tomography (OCT), embedded computing, machine learning, and AR/VR technologies. VETi is being developed for applications in retina care, digital health, identity security, cognitive science, and broader AI-enabled vision technologies. We are looking for a Senior Machine Learning Engineer to build the AI foundation for Kodiak’s VETi platform, from model research and training to deployment on embedded medical imaging hardware. This role is well suited for an engineer with strong machine learning and software fundamentals who enjoys complex computer vision problems and is excited to ship AI that runs on real wearable devices., * Lead the design, training, and deployment of machine learning models for wearable imaging and sensing systems - from research prototypes through production.

• Develop computer vision models for image processing and analysis across multiple imaging modalities and sensors.
• Analyze medical imaging data with deep learning models to support diagnostics and clinical decision-making.
• Build training pipelines, data labeling workflows, and evaluation frameworks that scale across imaging datasets.
• Integrate and optimize AI inference into the VETi platform’s real-time imaging and device-control stack, deploying to NPUs, GPUs, and embedded accelerators within latency, power, and memory budgets.
• Debug model accuracy and performance across training, evaluation, and on-device environments.
• Collaborate with electrical, optics, clinical, software, and systems engineering teams.

• B.S., M.S., or Ph.D. in AI, Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related technical discipline, or equivalent practical experience.
• 5+ years of professional machine learning experience developing and deploying production models.
• Strong programming experience in Python and C++, with at least one major ML framework (PyTorch, TensorFlow, or JAX) and solid software engineering practices.
• Strong deep learning experience, particularly in computer vision (CNNs, transformers, segmentation, detection, classification).
• Experience deploying models to edge devices, including model optimization (quantization, pruning, distillation) and inference runtimes (ONNX, TensorRT, or similar).
• Ability to collaborate across machine learning, software, hardware, scientific, and engineering teams.

Additional Experience That Would Be Valuable

• Experience with medical imaging data (OCT, fundus, retinal scans, MRI, CT, or similar).
• Experience working with 3D or volumetric imaging data (e.g., OCT B-scans, volumetric MRI/CT).
• Experience building AI agents for user interaction or human-in-the-loop systems.
• Experience with self-supervised learning, transfer learning, or other data-efficient methods for limited labeled data.
• Familiarity with regulated medical-device AI development (FDA SaMD, IEC 62304, ISO 13485), or willingness to learn.