[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All GE HealthCare Technologies jobs](https://jobs.opennash.com/companies/ge-healthcare-technologies/) · [Search jobs](/search/) GE HealthCare Technologies · Haifa, Haifa District, Israel # Staff Machine Learning Engineer Haifa, Haifa District, Israel Senior individual contributor Data & Analytics Listed on GE HealthCare Technologies’s official careers site. Posted June 24, 2026. Check that it is still open and apply there. [Apply on GE HealthCare Technologies’s careers site →](https://careers.gehealthcare.com/global/en/job/GEVGHLGLOBALR4042375EXTERNALENGLOBAL/Staff-Machine-Learning-Engineer) [OpenNash Jobs](https://jobs.opennash.com/) / [GE HealthCare Technologies](https://jobs.opennash.com/companies/ge-healthcare-technologies/) / Staff Machine Learning Engineer ## Job description ### Job Description Summary The Staff Machine Learning Engineer is a senior technical leader responsible for designing, developing, and deploying production-grade AI systems for GE Healthcare medical imaging products. This role focuses on vision-language models, diffusion models, and multimodal learning, working closely with data scientists, software engineers, product leaders, and clinical experts to turn advanced AI methods into robust product capabilities. The Staff Machine Learning Engineer is a senior technical leader responsible for designing, developing, and deploying production-grade AI systems for GE HealthCare medical imaging products. ### Key Responsibilities Design, implement, and productionize AI models for clinical applications, including vision and diffusion models. ### Own end-to-end model lifecycle data ingestion, training, evaluation, deployment, monitoring, and iteration. Work with large-scale medical datasets, ensuring data quality, preprocessing, and efficient pipeline management. Drive technical decisions and tradeoffs with a focus on scalability, maintainability, and real-world constraints. Collaborate with clinical AI scientists to translate research innovations into production-ready solutions. Stay current with advancements in vision-language modeling, GenAI, and related AI technologies. ### Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or related field. Significant hands-on experience building and deploying ML systems to production. Strong experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow). Solid understanding of deep learning, computer vision, and natural language processing techniques. Prior experience working with medical imaging data is highly preferred. Solid software engineering fundamentals, including testing, version control, CI/CD, and code reviews. Independent, self-learner, and results-oriented. Fluent English (speaking and writing). GE HealthCare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world. GE HealthCare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity. Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support. #LI-TM1 Additional Information The job is open to men and women equally Relocation Assistance Provided: No ## At a glance - Posted by the employer: Jun 24, 2026 - First seen by OpenNash: Jul 10, 2026 - Last checked: Oct 19, 2026 - Listed for: 117 days - Location: Haifa, Haifa District, Israel[Apply on GE HealthCare Technologies’s careers site →](https://careers.gehealthcare.com/global/en/job/GEVGHLGLOBALR4042375EXTERNALENGLOBAL/Staff-Machine-Learning-Engineer) ## More jobs at GE HealthCare Technologies ### [Algorithm Software Engineer](https://jobs.opennash.com/companies/ge-healthcare-technologies/jobs/b2b4c5406882e1d7db68/) Haifa, Haifa District, Israel ### [Algorithm Software Engineer- Medical Imaging](https://jobs.opennash.com/companies/ge-healthcare-technologies/jobs/dd67fb63b0b01503d376/) Haifa, Haifa District, Israel ### [Clinical Applications Engineer](https://jobs.opennash.com/companies/ge-healthcare-technologies/jobs/c6e28a3ecaf01fdd2edd/) Haifa, Haifa District, Israel ### [Lead Clinical Applications Engineer](https://jobs.opennash.com/companies/ge-healthcare-technologies/jobs/0eb3bc83363827878a9f/) Haifa, Haifa District, Israel ## Similar jobs at other companies ### [Engineer, Staff-Machine Learning-Embedded,C++](https://jobs.opennash.com/companies/qualcomm/jobs/36648b7095d4511c48c8/) Qualcomm · Hyderabad, Telangāna, India ### [Sr Staff/Principal DevOps Engineer, Machine Learning Infrastructure and Performance](https://jobs.opennash.com/companies/qualcomm/jobs/44797cbcd22659969f8e/) Qualcomm · Markham, Ontario, Canada ### [Machine Learning Engineer](https://jobs.opennash.com/companies/accenture/jobs/ef14ea91e804ba52f5de/) Accenture ### [Senior Machine Learning Engineer](https://jobs.opennash.com/companies/mercadolibre/jobs/1e3f1f34f8c59e73b38f/) MercadoLibre · Bogotá, Colombia ### [Quantitative / Machine Learning Engineer](https://jobs.opennash.com/companies/totalenergies/jobs/259a76019d5c03765816/) TotalEnergies OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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