Reliability Engineer II - Exempt

Join our team in Mounds View, MN, where innovation meets excellence. We are seeking a dedicated professional to ensure the safety, reliability, and performance of our products throughout their lifecycle. This role involves partnering with various teams to identify and mitigate risks, execute assessments, and drive improvements for enhanced patient outcomes and product performance.

Key Responsibilities

• Lead and support reliability activities for new product development and sustaining engineering projects.
• Develop and execute reliability strategies, plans, and test protocols aligned with product requirements and regulatory expectations.
• Conduct reliability analyses including Fault Tree Analysis (FTA), Failure Modes and Effects Analysis (FMEA), Design of Experiments (DOE), and statistical data analysis.
• Support cross-functional projects and programs.
• Collaborate with cross-functional teams to investigate failures, conduct root cause analyses, and implement corrective and preventive actions.
• Support Design Verification, Design Validation, and Design for Reliability (DfR) activities.
• Develop accelerated life testing and environmental stress testing methodologies.
• Evaluate supplier and manufacturing process reliability and identify areas for improvement.
• Prepare technical reports, presentations, and recommendations for management and project teams.
• Support regulatory submissions, audits, and compliance activities as required.
• Contribute to continuous improvement initiatives that enhance product quality, reliability, and operational efficiency.
• Mentor junior engineers and provide technical guidance on reliability methodologies and best practices.

Required Qualifications

• Bachelor's degree in Engineering (Mechanical, Electrical, Biomedical, Industrial, Packaging, or related field).
• Minimum of 2 years of engineering experience, including experience in reliability, quality, manufacturing, or product development.
• Experience applying statistical analysis techniques and reliability engineering principles.
• Knowledge of risk management and failure analysis methodologies.
• Strong problem-solving and analytical skills.
• Effective communication and collaboration skills.
• Ability to manage multiple projects and priorities in a fast-paced environment.

Preferred Qualifications

• Experience in the medical device, pharmaceutical, aerospace, automotive, or highly regulated industry.
• Knowledge of FDA, ISO 13485, IEC 60601, ISO 14971, or other applicable industry standards.
• Experience with Minitab, JMP, ReliaSoft, MATLAB, or similar statistical/reliability software tools.
• Experience leading cross-functional investigations and risk reduction initiatives.

Key Competencies

• Reliability Engineering
• Statistical Analysis
• Failure Analysis
• Risk Management
• Root Cause Investigation
• Design for Reliability
• Project Management
• Technical Communication
• Cross-Functional Collaboration
• Continuous Improvement

Responsibilities may include the following and other duties may be assigned. Develops, coordinates, and conducts technical reliability studies and evaluations of engineering design concepts and design of experiments (DOE) constructs. Recommends design or test methods and statistical process control procedures for achieving required levels of product reliability. Completes risk analysis studies of new design and processes. Compiles and analyzes performance reports and process control statistics; investigates and analyzes relevant variables potentially affecting product and processes. Ensures that corrective measures meet acceptable reliability standards. Analyzes preliminary plans and develops reliability engineering programs to achieve company, customer, and governmental agency reliability objectives. May develop mathematical models to identify units, batches, or processes posing excessive failure risks. As necessary, proposes changes in design or formulation to improve system and/or process reliability. May determine units and/or batches requiring environmental testing, and specifies minimum number of samples to obtain statistically valid data.