Biomedical Product Engineer, Sr. Staff

Siemens Healthineers

23h

About The Position

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. Join our team now at Siemens Healthineers Diagnostics as a Staff Systems Engineer in Biomedical Product Design in the Core Lab Solutions (CLS) R&D System Engineering organization within the Diagnostics business. The System Engineering (SE) organization is the technical hub for integrating the chemistries, mechanics, optics, fluidics, robotics, and control systems to develop and launch new products for the CLS business line. This role can be located in Newark, DE or Tarrytown, NY and reports into the System Architecture & Design (SAD) organization within the SE organization. This is a role well suited to an ambitious experienced professional, looking for the next step in their career. We are seeking a Sr. Staff Systems Engineer to serve as a technical pillar within the System Architecture & Design (SAD) organization. As a senior-level leader, you will be a visionary force in the development of complex, multi-disciplinary analytical medical instrument systems. You will not only contribute to the design of hardware-software integrated electromechanical instruments but will also define the technical roadmap and architectural standards for our next-generation CLS product portfolio.

Requirements

Bachelor’s degree in Biomedical Engineering or similar engineering discipline (ex. Optical, mechanical, chemical, electrical, computer, or system engineering)
Minimum of 20 years of Systems/Optical Engineering, and/or Integrated Hardware-Software Design engineering experience in product development environment
Minimum of 15 years of technical and product design and development experience in medical device industry
Minimum of 5 years of experience in Model Based Systems Engineering
Minimum of 5 years of experience in Modeling/Simulation tools
Proficiency in design and analysis using ZEMAX or similar software; familiarity with both imaging and non-imaging illumination design
Systems Thinking
Learning mindset
Critical and clear thinker
Strong interpersonal and written/verbal communication skills

Nice To Haves

Master’s or PhD degree in Engineering
This role demands significant hands-on experience with optics, sensors, and imaging systems, emphasizing experimental work, quick prototyping, and laboratory-based development.
Extensive development and application experience in a MBSE framework
Extensive systems and design engineering experience in complex electro-opto-mechanical instrumentation for medical/imaging applications in a new product development environment
Extensive experience with medical device product lifecycle
Deep practice in Design for Reliability (reliability requirements allocation, fault-tolerant systems, physics of failure, reliability statistics, reliability modeling and prediction)
Expert level knowledge and demonstrated capabilities with modern design methodologies, code generation, and associated tools (e.g., Root cause analysis, dFMEA, Design of Experiment, ML/AI)
Demonstrated ability to lead and collaborate with technical teams and drive results and outcomes.
Experience working with large cross-functional multidisciplinary teams in matrixed organization.
Expert level knowledge of statistical techniques and/or Six Sigma methodologies
Knowledge and experience in Scrum/Agile product development

Responsibilities

Comfortable and adept in working in the following primary domains: Mechanical, Electrical, Fluidic, Thermal, Optical, Low-Level Real Time Control Firmware, High-Level Object-Oriented Software.
Work with cross-functional teams (Marketing, Service, Mechanical Engineering, Electrical Mechanical Engineering, Software Engineering, Manufacturing) in developing design concepts for new products.
Partner with stakeholders to define Voice of Customer (VoC) inputs, clinical needs, and regulatory standards into clear, actionable use cases and system requirements and specifications for the CLS business.
Oversee comprehensive Usability Assessments and Human Factors Engineering throughout the development lifecycle (Formative and Summative testing).
Oversee comprehensive safety risk management activities (e.g., Hazard Analysis, FTA, dFMEA) by systematically identifying, documenting, and tracking system-level risks.
Oversee the design and execution of laboratory experiments to evaluate feasibility of medical instrument system, subsystem and component design concepts.
Oversee the execution of subsystem and system design characterization and performance testing to assess, debug, and optimize the integrated operation of complex subsystems.
Lead the development of instrument features, system integration efforts, assisting cross-functional teams to resolve subsystem to subsystem interface issues and ensure seamless function between hardware and software subsystems.
Direct trade-off studies and analyses to evaluate and select optimal technical solutions based on cost, performance, and risk.
Lead the design and development of AI agents that coordinate cross-functional workflows, enabling intelligent automation and streamlined decision support across product development.
Provide subject matter expertise to determine root cause of system/assay performance issues and propose design modifications.
You will work closely with Structured Testing and Practices (STP) organization to develop/review testing plans and protocols and provide troubleshooting and data analysis support during execution.
Mentor other engineers on Model Based Systems Engineering and expand the use of modeling simulation tools within the engineering communities.
Excel in communication and keeping development teams aligned.
Excel in presenting information to a leadership audience.
Excel in creation and analysis of complex models to support effective decision making.