Machine Operator - Remote Opportunities Available
About the Role
We're hiring a Machine Operator to join our dynamic team at Nexans. This role offers the opportunity to work remotely while contributing to our mission of electrifying the future. As a Machine Operator, you'll play a crucial role in ensuring the efficiency and quality of our production processes.
What You'll Do
- Conduct production machines in line with objectives in quantity, quality, and deadlines.
- Perform quality checks on products and report non-conformities and breakdowns.
- Monitor machine performance and productivity, alerting on failures, risks, and problems.
- Apply safety and environmental standards within the workplace.
- Engage in 5S practices and autonomous maintenance to maintain a safe environment.
Requirements
- Minimum Technical degree or equivalent.
- Previous experience in the industrial field is preferable.
- Strong teamwork and commitment skills.
- Fluency in French or English.
- Ability to work independently and take initiative.
Nice to Have
- Experience with production machinery.
- Knowledge of safety and environmental standards.
- Problem-solving skills.
What We Offer
- Competitive salary and benefits package.
- Opportunities for professional growth and development.
- Supportive and inclusive work environment.
- Flexible work arrangements, including remote work options.
- Engagement in a culture of knowledge sharing and teamwork.
This Machine Operator role at Nexans offers remote work opportunities and a chance to contribute to sustainable energy solutions. Join a supportive team and grow your career.
Who Will Succeed Here
Proficient in operating production machinery such as CNC machines or automated assembly lines, with a solid understanding of how to troubleshoot mechanical issues.
Self-motivated and disciplined, able to manage time effectively in a remote work environment while maintaining focus on quality control and safety standards.
Analytical mindset with a strong problem-solving ability, capable of identifying production inefficiencies and suggesting improvements based on quality data.
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