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About Us Medical Image Insights is building AI infrastructure for the future of medical imaging. Our work includes medical imaging foundation models, multimodal image-text learning, AI-assisted diagnosis, automated radiology report generation, lesion detection, segmentation, image-report alignment, and clinical AI product deployment. Our MIIA platform is designed to support the full medical imaging AI lifecycle, from data governance, annotation, model training, validation, and evaluation to hospital deployment and clinical workflow integration. As we establish our Hong Kong office, we are looking for a strong AI engineer who can help develop and productize advanced medical imaging AI for international markets. The Role We are looking for a Senior Machine Learning Engineer focused on multimodal medical imaging AI. You will work on large-scale medical imaging foundation models, image-report alignment, report generation, lesion detection, segmentation, visual pretraining, model fine-tuning, and hospital-facing AI applications. This role requires both research ability and engineering execution. You should be able to read frontier research, design experiments, implement ideas quickly, evaluate model performance rigorously, and help turn models into reliable products. Responsibilities Participate in the design, training, validation, and optimization of large-scale medical imaging foundation models. Work on multimodal medical imaging tasks, including image-text alignment, report generation, lesion detection, classification, segmentation, and clinical finding extraction. Improve model performance for real-world hospital applications using methods such as supervised fine-tuning, reinforcement learning, prompt engineering, data iteration, post-training, and evaluation-driven optimization. Build and improve automated data iteration, model training, model evaluation, and model deployment pipelines. Work with large-scale medical imaging and report datasets, including data preprocessing, visualization, statistics, quality control, and dataset construction. Collaborate with software engineers to build stable and efficient inference and deployment systems. Work with doctors and clinical experts to define clinically meaningful model outputs, evaluation standards, and product workflows. Track frontier research in computer vision, medical image analysis, multimodal models, VLMs, LLMs, and medical AI, and apply relevant innovations to company projects. Contribute to technical documentation, project documentation, internal knowledge bases, patents, papers, and international AI challenges where appropriate. Collaborate closely with the mainland China R&D team and support Hong Kong/international project delivery. Requirements Master’s degree or above in Computer Science, Artificial Intelligence, Biomedical Engineering, Medical Image Analysis, Machine Learning, or a related field. A PhD is strongly preferred, especially with research experience in computer vision, multimodal AI, or medical imaging AI. Strong hands-on experience in computer vision, multimodal AI, visual pretraining, medical imaging AI, or foundation models. Solid programming skills in Python and strong experience with PyTorch or another major deep learning framework. Strong understanding of deep learning model training, validation, metrics, data preprocessing, and experiment design. Experience with 2D or 3D medical imaging data, such as CT, MRI, X-ray, or PET. Strong engineering ability and the ability to quickly implement, test, and improve technical ideas. Strong learning ability, problem-solving ability, and confidence in tackling difficult technical challenges. Clear communication skills and the ability to explain technical ideas, methods, progress, and results in a structured way. Nice to Have Experience in medical imaging report generation, image-report alignment, radiology VLMs, or post-training of multimodal models. Experience with MAE, Vision Transformers, CLIP-style models, LLMs, VLMs, SFT, reinforcement learning, CoT construction, prompt engineering, or model evaluation. Experience with MONAI, nnU-Net, DICOM, NIfTI, 3D CNNs, distributed training, model serving, or GPU inference optimization. Strong record in international medical AI competitions, top-tier conference/journal publications, impactful open-source projects, or applied medical imaging AI products. Experience working with radiologists, hospitals, clinical validation, or healthcare AI productization. Mandarin Chinese for close collaboration with our China-based R&D, product, and clinical teams. Compensation HK$63,333–95,000 per month, depending on experience and qualifications. Exceptional candidates with highly relevant medical imaging AI or multimodal AI experience may be considered above this range. Work visa sponsorship is available for the right candidate, including applicants from mainland China and overseas. Why Join Us Join the early AI team of our Hong Kong office and help build Yinghe’s international AI capability. Work on medical imaging foundation models, multimodal AI, image-report alignment, report generation, and clinical AI deployment. Work with large-scale real-world medical imaging data and clinical scenarios, supported by one of China’s leading nationwide medical imaging service networks. Build AI systems that move from research to real hospital-facing products. Collaborate with doctors, AI researchers, software engineers, product teams, and international partners. Contribute to international research collaborations, technical publications, AI challenges, product development, and global medical AI deployment. Help define the next generation of medical imaging AI products for international markets. Competitive compensation, with equity available for exceptional candidates and visa support for relocating talent.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.