below marketmost similar roles pay hereabove market
This role pays less than
80%
of similar roles. Most pay
$187,850–$254,750
— the blue band above.
At the midpoint, this role pays about
$183k
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.
JOB TITLE: AI/ML Scientist – Reinforcement Learning, Simulation & Optimization
The AI Scientist – Reinforcement Learning & Operational Twinning joins the Digital Technology & Innovation organization to develop next-generation AI systems for healthcare operations. This role focuses on expanding operational twinning research by designing reinforcement learning, simulation, and optimization algorithms. You will build intelligent decision-making systems to optimize scheduling, patient flow, triage, and resource utilization within complex healthcare environments. Key responsibilities include conducting original research in sequential decision-making, combinatorial optimization, and hybrid AI–operations research methods while translating large-scale datasets into actionable policy-learning solutions. You will utilize Python and modern ML frameworks like PyTorch, TensorFlow, or JAX to prototype and validate scalable models. The work addresses the technical challenge of modeling real-world clinical workflows within dynamic virtual environments to improve hospital efficiency and patient outcomes.
Design and develop reinforcement learning, simulation, and optimization algorithms for healthcare Operational Twinning applications.
Build intelligent decision-making systems to optimize scheduling, patient flow, triage, staffing, and resource utilization.
Develop AI-driven simulation environments and workflow models that represent real-world clinical and operational systems.
Conduct original research in reinforcement learning, sequential decision-making, combinatorial optimization, and hybrid AI–operations research methods.
Translate large-scale healthcare datasets into actionable optimization and policy-learning solutions.
Prototype, evaluate, and validate novel algorithmic approaches for feasibility, scalability, explainability, and operational impact.
Integrate advanced optimization and simulation technologies into Siemens Healthineers’ digital health platforms.
Publish scientific research and contribute to patents to drive innovation in operational AI and healthcare technologies.
What we're looking for
Ph.D. in Computer Science, Applied Mathematics, Operations Research, Electrical Engineering, Robotics, Artificial Intelligence, or a related technical field.
Strong hands-on experience in reinforcement learning, sequential decision-making systems, or simulation-based optimization.
Experience developing optimization algorithms, operational AI systems, or digital twin/simulation environments.
Strong programming skills in Python and modern ML frameworks such as PyTorch, TensorFlow, or JAX.
Experience translating complex real-world operational problems into scalable AI-driven solutions.
Strong technical communication skills and demonstrated research contributions through publications, patents, or applied research projects.
Experience with digital twins, workflow simulation, world models, or autonomous systems (preferred).
Python
PyTorch
JAX
TensorFlow
Reinforcement Learning
LLM Agents
Kubernetes
Ray
Slurm
CUDA
ROCm
HIP
Distributed Systems
Data Pipelines
Model Serving
Profiling
Compilers
Simulators