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- Tasks: Lead the development of cutting-edge vision systems for quality control in manufacturing.
- Company: Proclinical is a top life sciences recruiter connecting talent with global opportunities.
- Benefits: Gain hands-on experience in a dynamic field with potential for growth and innovation.
- Why this job: Join a team that values creativity and problem-solving while making an impact in manufacturing.
- Qualifications: Experience in automated vision systems and proficiency with platforms like Cognex Designer required.
- Other info: Contact Indre Stankeviciute for questions or apply directly to seize this opportunity!
The predicted salary is between 36000 - 60000 £ per year.
Proclinical is recruiting for a skilled Engineer for Machine Vision Systems. This role will lead the development and enhancement of vision systems for manufacturing quality control. The successful candidate will need to focus on designing, implementing, and validating systems that integrate product metadata with dimensional measurements.
Responsibilities:
- Design and specify vision hardware, including sensors, lenses, and lighting.
- Collaborate with automation teams to create mechanical solutions for inspection stations.
- Develop user interfaces and imaging recipes for inspection systems.
- Program interfaces between system components such as PC, controller, camera, and lighting.
- Implement strategies for data naming, storage, and upload to ensure traceability and accessibility.
- Define and deploy high-volume manufacturing solutions for vision system integration.
- Lead the validation and scaling of pilot systems into full production environments.
- Test and validate system performance to meet production and quality requirements.
- Troubleshoot and optimize hardware/software for reliability and throughput.
Key Skills and Requirements:
- Proven working history in automated vision systems within a manufacturing environment.
- Proficiency with platforms like Cognex Designer.
- Strong knowledge in vision hardware and software integration.
- Strong understanding of data pipelines and quality control processes.
- Experience in developing and implementing vision systems for dimensional and quality measurement.
If you are having difficulty in applying or if you have any questions, please contact Indre Stankeviciute on
Apply Now:
If you are interested in learning more or applying to this exciting opportunity, please complete the form below and attach a copy of your CV. Alternatively, for further details or to talk directly to a life sciences recruitment specialist, please request a call back at the top of this page.
Proclinical is a leading life sciences recruiter focused on finding exceptional people and matching them with the finest positions across the globe. Proclinical is acting as an Employment Agency in relation to this vacancy.
Machine Vision Systems Engineer employer: Proclinical Staffing
Contact Detail:
Proclinical Staffing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Vision Systems Engineer
✨Tip Number 1
Make sure to showcase your experience with automated vision systems in your conversations. Highlight specific projects where you designed or implemented vision systems, especially in manufacturing environments.
✨Tip Number 2
Familiarize yourself with the tools and platforms mentioned in the job description, like Cognex Designer. If you have experience with similar software, be ready to discuss how those skills can transfer to this role.
✨Tip Number 3
Prepare to discuss your understanding of data pipelines and quality control processes. Think of examples where you successfully integrated these elements into a vision system.
✨Tip Number 4
Network with professionals in the field of machine vision systems. Attend relevant industry events or online forums to connect with others who may provide insights or referrals for this position.
We think you need these skills to ace Machine Vision Systems Engineer
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description for the Machine Vision Systems Engineer position. Make sure you understand the key responsibilities and required skills, as this will help you tailor your application.
Highlight Relevant Experience: In your CV and cover letter, emphasize your proven working history in automated vision systems within a manufacturing environment. Be specific about your experience with platforms like Cognex Designer and any relevant projects you've worked on.
Showcase Technical Skills: Clearly outline your technical skills related to vision hardware and software integration. Mention any experience you have with data pipelines and quality control processes, as these are crucial for the role.
Craft a Strong Cover Letter: Write a compelling cover letter that not only summarizes your qualifications but also expresses your enthusiasm for the role. Discuss how your background aligns with the responsibilities of designing, implementing, and validating vision systems.
How to prepare for a job interview at Proclinical Staffing
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with automated vision systems in detail. Highlight specific projects where you designed or implemented vision hardware, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Collaboration Skills
Since this role involves working closely with automation teams, share examples of past collaborations. Discuss how you contributed to creating mechanical solutions for inspection stations and how you ensured effective communication among team members.
✨Prepare for Problem-Solving Questions
Expect questions that assess your troubleshooting abilities. Think of scenarios where you had to optimize hardware or software for reliability and throughput, and be ready to walk through your thought process and the outcomes.
✨Understand Data Management Strategies
Familiarize yourself with data naming, storage, and upload strategies. Be prepared to discuss how you ensure traceability and accessibility of data in your previous roles, as this is crucial for quality control processes.
