Agilent Technologies
Manufacturing Engineer
US-DE-Newport · Mid · Full-time
Sponsorship not specified$103k-$161kDetected 3 days ago
AccessibilityProject ManagementProcess ImprovementProcurementPLCMechanical DesignMass SpectrometryCommunicationCollaborationProblem SolvingLean Manufacturing
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odds of building a lasting career here
54Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role78
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
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About the role
- This position plays a critical role in improving safety, quality, productivity, and manufacturing capacity while ensuring reliable operation of chemical processing and automated production systems.
- Present project updates, recommendations, risks, and project milestones to management and project stakeholders.
Responsibilities
- Provide day-to-day engineering support for silica manufacturing operations used in HPLC column production.
- Partner with Chemistry and Production teams to support silica functionalization processes and drive continuous improvements.
- Lead and/or support cross-functional capital projects focused on improving operational safety, capacity, quality, reliability, and financial performance.
- Manage project schedules, budgets, resources, and execution timelines to ensure successful project completion.
- Develop equipment requirements, technical specifications, and design documentation in collaboration with process engineering and chemistry teams.
- Participate in equipment cut sheet reviews, facility layout reviews, and P&ID design reviews.
- Troubleshoot manufacturing equipment and process issues, identify root causes, and implement corrective actions.
- Provide engineering support to the maintenance team on equipment reliability, repairs, upgrades, and preventive maintenance initiatives.
- Support validation, qualification, and commissioning activities for new manufacturing equipment and processes.
- Drive continuous improvement initiatives utilizing Lean Manufacturing and problem-solving methodologies.
Requirements
- Bachelor's degree in mechanical engineering, Chemical Engineering, Manufacturing Engineering, or a related engineering discipline.
- 4+ years of manufacturing engineering experience in a chemical, pharmaceutical, life sciences, analytical instrumentation, or related manufacturing environment.
- Knowledge of chemical processing systems, mechanical equipment, and industrial manufacturing practices.
- Experience managing engineering projects, including budget and schedule responsibility.
- Required Qualifications
- Experience supporting manufacturing processes, equipment design, and equipment troubleshooting.
Nice to have
- Knowledge of process equipment used in chemical manufacturing environments
- Experience working with PLC-controlled automated systems and industrial controls.
- Experience reviewing P&IDs, process flow diagrams, and manufacturing facility layouts.
- Lean Manufacturing, Six Sigma, or continuous improvement experience.
- Experience supporting capital equipment procurement, installation, and commissioning.
- Key Competencies
- Process Engineering
- Capital Project Management
Skills
- Strong analytical, problem-solving, and root cause analysis skills.
- Excellent communication and collaboration skills with cross-functional teams.
Compensation
- The full-time equivalent pay range for this position is $103,200.00 - $161,250.00/yr plus eligibility for bonus, stock and benefits.
Benefits
- Lead design reviews and project meetings with Production, Engineering, Maintenance, Health & Safety, Workplace Services, and other stakeholders.
Company info
- If you have a disability and need assistance with any part of the application or interview process or have questions about workplace accessibility, please email job_posting@agilent.com or contact +1-262-754-5030.
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This listing is sourced directly from Agilent Technologies's careers page and normalized into a canonical job model.