below marketmost similar roles pay hereabove market
This role pays less than
90%
of similar roles. Most pay
$187,762–$254,750
— the blue band above.
At the midpoint, this role pays about
$153k
versus about
$221k
for comparable roles.
Based on 240 similar postings.
Employer
About Siemens Healthineers
Siemens Healthineers is a leading global medical technology company, headquartered in Germany, that provides imaging, diagnostics, and artificial intelligence-driven solutions to healthcare providers.
Siemens Healthineers currently has
41 open roles
on FindRole.
Listed pay typically runs
$129,900–$178,618
across 41 roles with salary data.
The Foundation AI Research Scientist joins a team dedicated to advancing next-generation multimodal foundation models for healthcare. In this role, you will research, design, and develop large-scale AI models capable of reasoning across complex medical data, including medical imaging, clinical text, electronic health records, and real-time monitoring data. You will explore state-of-the-art approaches in vision-language learning, model distillation, few-shot and zero-shot learning, and generative AI to accelerate clinical capabilities. Key responsibilities include developing innovative architectures for model generalization, robustness, and interpretability while translating research prototypes into scalable technologies for real-world clinical environments. You will utilize modern deep learning frameworks to solve technical problems in medical AI, ensuring systems meet clinical-grade performance expectations and safety requirements across diverse patient populations and healthcare institutions worldwide.
Design and develop large-scale multimodal foundation models for healthcare and medical imaging applications.
Research next-generation AI architectures and learning strategies to improve downstream clinical performance.
Develop innovative model distillation, transfer learning, few-shot, and zero-shot learning approaches.
Advance multimodal AI capable of learning across medical images, clinical text, and patient history.
Design methods to improve model generalization, robustness, uncertainty awareness, and interpretability in clinical environments.
Translate research prototypes and novel AI methodologies into scalable technologies for real-world clinical workflows.
Advance research in AI safety, reliability, and responsible AI principles for clinical-grade performance.
Publish impactful research in leading journals and conferences and identify opportunities for new intellectual property.
What we're looking for
PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related technical field with research in machine learning, AI, computer vision, or medical imaging.
Demonstrated research experience developing advanced machine learning or deep learning models.
Strong understanding of modern deep learning architectures and training methodologies.
Experience with foundation models, multimodal learning, vision-language models, generative AI, or self-supervised/representation learning.
Experience with few-shot/zero-shot learning, model distillation, or 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.
Multimodal Foundation Models
LLMs
Large Vision-Language Models
Diffusion Algorithms
Action-based Transformers
PyTorch
Jax
TensorFlow
Python
C++
CUDA
Reinforcement Learning
Imitation Learning
ROS
Robot Kinematics
Model Predictive Control
MuJoCo
Isaac Sim
Whole-body Control
Python
PyTorch
JAX
Deep Learning
Generative AI
Multimodal Foundation Models
Computer Vision
Data Pipelines
On-device Machine Learning
Data Curation
Vision-Language Models
Video-Language Models
Python
PyTorch
TensorFlow
Deep Learning
Reinforcement Learning
LLMs
Probabilistic Modeling
Causal Inference
Multi-Agent Systems
Neuro-symbolic AI
Time-series Forecasting
Simulation-based Planning
Model Training
Data Science
Machine Learning