Reliability Technician - Life Sciences Plant (Contract)

QCS Staffing Ltd; Kentucky; On-site; USD 52,000 - 78,000; Full time

Job summary

QCS Staffing Ltd is seeking a Reliability Technician for an Ohio-based Life Sciences project on an initial 12-month contract. The role focuses on performing FMEAs, interpreting engineering drawings, and developing maintenance strategies for a new-build facility.

The candidate will use AI-assisted tools to draft FMEA content and refine it for technical accuracy, identifying credible failure modes and proposing preventive, predictive, and run-to-failure approaches to maintain equipment reliability.

Qualifications

• Experience in a manufacturing, chemical-processing, utilities or comparable industrial plant environment.
• Direct experience completing or contributing to equipment FMEAs, maintenance strategies or reliability analyses.
• Ability to read P&IDs, equipment drawings or electrical diagrams to identify equipment and relationships.
• Experience with pumps, electric motors and variable-frequency drives, including common failure modes.

Responsibilities

• Complete baseline FMEAs for facility, utility and manufacturing systems using drawings and OEM manuals.
• Use AI-assisted tool to generate initial FMEA content and validate for technical accuracy.
• Identify credible failure modes, causes, effects and consequences for equipment and systems.
• Develop preventive, predictive, condition-based and run-to-failure maintenance recommendations.

Skills

Manufacturing environment experience

FMEA participation

Reading engineering diagrams

Pumps, motors & VFDs knowledge

Job description

QCS Staffing Ltd is seeking a Reliability Technician for an Ohio-based Life Sciences project on an initial 12-month contract. The role focuses on performing FMEAs, interpreting engineering drawings, and developing maintenance strategies for a new-build facility.

The candidate will use AI-assisted tools to draft FMEA content and refine it for technical accuracy, identifying credible failure modes and proposing preventive, predictive, and run-to-failure approaches to maintain equipment reliability.