Foundation AI Research Scientist

Aimlroles; Precinct (MA); On-site; USD 129,000 - 177,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) retirement plan

Life insurance

Disability insurance

Paid parking/public transportation

Paid time off

Paid sick time

Job summary

Siemens Healthineers is seeking a Foundation AI Research Scientist to advance multimodal foundation models for healthcare, including medical imaging and clinical data. You will design, train, and evaluate models that learn across images, text, and patient history, collaborating with AI scientists, engineers, and clinicians.

You will explore novel architectures, distillation, and few-/zero-shot learning to scale AI capabilities across medical findings.

Qualifications

• PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or related field.
• Demonstrated research in ML/DL.
• Strong understanding of modern DL architectures and training methods.
• Experience with foundation models and multimodal learning.
• Familiarity with medical imaging AI.
• Excellent programming skills in deep learning frameworks.

Responsibilities

• Designing and developing large-scale multimodal foundation models for healthcare.
• Researching next-generation AI architectures and learning strategies.
• Developing model distillation, transfer learning, and few-shot/zero-shot methods.
• Advancing multimodal AI across medical images, text, and health data.
• Collaborating with researchers, engineers, and clinicians to deploy systems.

Skills

Foundation models

Multimodal learning

Vision-language models

Medical imaging AI

Deep learning

Model distillation

Few-shot learning

Zero-shot learning

Scientific communication

Education

PhD in CS/EE/BME

Strong ML/DL background

Tools

PyTorch

TensorFlow

Job description

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions.

Siemens Healthineers is seeking a Foundation AI Research Scientist to advance the development of next-generation multimodal foundation models for healthcare.

In this role, you will research, design, and develop large-scale AI models capable of learning and reasoning across complex medical data, including medical imaging, clinical text, electronic health records, real-time monitoring data, and other healthcare information.

You will explore state-of-the-art approaches in multimodal foundation models, vision-language learning, model distillation, few- and zero-shot learning, and next-generation AI architectures to dramatically accelerate the development of new clinical AI capabilities and enable systems that can scale across hundreds of findings and use cases.

Working at the intersection of foundational AI research and clinical application, you will collaborate closely with AI scientists, software engineers, and clinical experts to translate breakthrough research into scalable technologies that can ultimately support clinical workflows worldwide.

You are responsible for:

Foundation AI Research & Development

• Designing and developing large-scale multimodal foundation models for healthcare and medical imaging applications.
• Researching next-generation AI architectures and learning strategies capable of delivering significant improvements in downstream clinical performance.
• Developing innovative model distillation, transfer learning, few-shot, and zero-shot learning approaches to accelerate expansion of AI capabilities across a broad range of clinical findings and use cases.
• Advancing multimodal AI capable of learning across medical images, clinical text, patient history, and other healthcare data sources.
• Exploring approaches that move AI systems toward increasingly autonomous capabilities supporting clinical decision-making, workflow automation, and personalized patient care.
• Designing methods to improve model generalization, robustness, uncertainty awareness, interpretability, and reliability in complex clinical environments.
• Staying at the forefront of developments in foundation models, multimodal learning, computer vision, generative AI, and medical AI research.

Clinical AI Translation & Integration

• Collaborating closely with AI researchers, software engineers, clinical experts, and product teams to connect foundational AI research with real-world healthcare applications.
• Supporting the integration of multimodal AI systems incorporating medical imaging, electronic health records, clinical text, real-time monitoring, and other healthcare data.
• Translating research prototypes and novel AI methodologies into scalable approaches suitable for real-world clinical environments.
• Helping enable the transition of advanced AI technologies from research into solutions capable of deployment across healthcare institutions worldwide.

AI Safety, Reliability & Responsible AI

• Advancing research in AI safety, reliability, robustness, and interpretability for clinical AI systems.
• Developing approaches that help ensure foundation models perform reliably across diverse patient populations, clinical environments, and data distributions.
• Supporting the development of AI technologies aligned with clinical-grade performance expectations, responsible AI principles, and applicable healthcare requirements.
• Contributing technical expertise toward evolving healthcare AI regulations and emerging AI safety frameworks.

Scientific Leadership & Innovation

• Publishing impactful research in leading journals and conferences such as TPAMI, Medical Image Analysis (MedIA), IEEE Transactions on Medical Imaging (TMI), CVPR, ICCV, ECCV, and other relevant venues.
• Identifying opportunities for novel intellectual property and contributing to patent development.
• Collaborating with internal and external research communities to advance the state of the art in foundation AI for healthcare.

Required Qualifications:

• PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related technical field with research focused on machine learning, artificial intelligence, computer vision, medical imaging, or a closely related discipline.
• Demonstrated research experience developing advanced machine learning or deep learning models.
• Strong understanding of modern deep learning architectures and training methodologies.
• Experience with one or more areas such as:
• Foundation models and large-scale pretrained models
  • Multimodal learning
  • Vision-language models
  • Computer vision
  • Generative AI
  • Self-supervised or representation learning
  • Few-shot or zero-shot learning
  • Knowledge/model distillation
  • Medical imaging AI
• Strong programming skills and experience using modern deep learning frameworks.
• Ability to translate emerging research concepts into practical AI systems and experimental prototypes.
• Strong scientific communication and cross-functional collaboration skills.
• Exceptional candidates with a Master’s degree and significant research or industry experience developing advanced AI systems will also be considered.

Preferred Qualifications

• Research experience with large-scale multimodal or vision-language foundation models.
• Experience pretraining, fine-tuning, adapting, or evaluating large AI models.
• Experience developing AI models using medical imaging or other healthcare data.
• Experience with model compression, knowledge distillation, parameter-efficient adaptation, or related techniques.
• Experience with self-supervised learning, weakly supervised learning, few-shot learning, or zero-shot generalization.
• Experience evaluating model robustness, uncertainty, interpretability, or safety.
• Strong publication record at leading AI, computer vision, or medical imaging conferences and journals.
• Experience translating research into production or clinically relevant AI systems.
• Track record of innovation demonstrated through publications, patents, open-source contributions, or deployed AI technologies.

Who we are: We are a team of more than 72,000 highly dedicated Healthineers in more than 70 countries. As a leader in medical technology, we constantly push the boundaries to create better outcomes and experiences for patients, no matter where they live or what health issues they are facing. Our portfolio is crucial for clinical decision-making and treatment pathways.

How we work:

When you join Siemens Healthineers, you become one in a global team of scientists, clinicians, developers, researchers, professionals, and skilled specialists, who believe in each individual’s potential to contribute with diverse ideas. We are from different backgrounds, cultures, religions, political and/or sexual orientations, and work together, to fight the world’s most threatening diseases and enable access to care, united by one purpose: to pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably.

The base pay range for this position is:

$128,700 - $176,957

Factors which may affect starting pay within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate.

If this is a commission eligible position the commission eligibility will be in accordance with the terms of the Company's plan. Commissions are based on individual performance and/or company performance.

• medical insurance
• dental insurance
• vision insurance
• 401(k) retirement plan.
• life insurance
• long-term and short-term disability insurance
• paid parking/public transportation
• paid time off
• paid sick and safe time.

Equal Employment Opportunity Statement:

Siemens Healthineers is an Equal Opportunity and Aff

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Siemens Healthineers is committed to equal employment opportunity. As part of this commitment, we will ensure that persons with disabilities are provided reasonable accommodations.

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Export Control:

A successful candidate must be able to work with controlled technology in accordance with US export control law. It is Siemens Healthineers’ policy to comply fully and completely with all United States export control laws and regulations, including those implemented by the Department of Commerce through the Export Administration Regulations (EAR), by the Department of State through the International Traffic in Arms Regulations (ITAR), and by the Treasury Department through the Office of Foreign Assets Control (OFAC) sanctions regulations.

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