Remote Intelligent Systems Engineering Jobs in Plainfield, NJ

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably.
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Join Siemens Healthineers' Digital Technology & Innovation (DTI) organization as an AI Scientist - Reinforcement Learning & Operational Twinning, where you will develop next-generation AI systems that optimize healthcare operations through intelligent simulation, sequential decision-making, and digital twin technologies.

In this role, you will help expand and operationalize Siemens Healthineers' Operational Twinning research initiatives across complex healthcare environments. Your work will directly influence how hospitals and health systems improve patient flow, resource allocation, scheduling, capacity management, and operational efficiency at scale. Working at the intersection of reinforcement learning, operations research, simulation, and digital twins, you will design intelligent systems capable of modeling and optimizing real-world healthcare workflows within dynamic virtual environments. This role is ideal for candidates passionate about sequential decision systems, AI-driven simulations, and operational optimization challenges with meaningful real-world impact.

You will collaborate closely with cross-functional R&D, engineering, and clinical teams to translate advanced research into scalable production-ready solutions that improve healthcare accessibility, efficiency, and patient outcomes worldwide.

You are responsible for:

• Designing and developing reinforcement learning, simulation, and optimization algorithms for Operational Twinning applications in healthcare.

• Building intelligent decision-making systems that optimize scheduling, patient flow, triage, staffing, and resource utilization across complex healthcare environments.

• Developing AI-driven simulation environments and workflow models capable of representing real-world clinical and operational systems.

• Conducting original research in reinforcement learning, sequential decision-making, combinatorial optimization, neural optimization, and hybrid AI-operations research (AI-OR) methods.

• Translating large-scale operational and healthcare datasets into actionable optimization and policy-learning solutions.

• Rapidly prototyping, evaluating, and validating novel algorithmic approaches for feasibility, scalability, explainability, and operational impact.

• Collaborating with multidisciplinary R&D teams to integrate advanced optimization and simulation technologies into Siemens Healthineers' digital health platforms.

• Publishing scientific research, contributing to patents, and driving innovation in operational AI and healthcare optimization technologies.

• Staying current with advancements in reinforcement learning, world models, AI simulation, operations research, and autonomous decision systems.

Required Qualifications

• 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.

Preferred Qualifications

• Experience with digital twins, workflow simulation, world models, or autonomous systems.

• Background in operations research, combinatorial optimization, stochastic systems, or control theory.

• Familiarity with healthcare operations, hospital systems, or clinical workflow optimization.

• Experience deploying AI solutions into production or cloud-based environments (AWS, Azure, GCP).

• Industry or applied research experience developing operational AI systems at scale.

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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.

To find out more about Siemens Healthineers businesses, please visit our company page here.

The base pay range for this position is:

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.

The Company offers the following benefits for this position, subject to applicable eligibility requirements: 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 Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.

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