Manufacturing Automation Engineer

Polyvinyl Films, Inc.
Greater London
2 months ago
Applications closed

Related Jobs

View all jobs

Automation Engineer

Vision Systems Engineer

Director of Artificial Intelligence - Manufacturing & Industrial

Software Engineer

AI & Data Engineer - KTP Associate

Senior Data Scientist, Quantitative Biosciences

The Manufacturing Automation Engineer at Polyvinyl Films Inc. is responsible for designing and optimizing manufacturing equipment and processes to improve production efficiency, ensuring the quality of products in a blown plastic films manufacturing environment. This role will also include process engineering responsibilities, where the engineer will assess and refine production workflows, troubleshoot issues with machinery, and implement improvements to achieve production goals and maintain high product quality. This role focuses on improving efficiency, reducing waste, and enhancing quality through automation technologies, PLC programming, robotics, and data-driven process improvements.

RESPONSIBILITIES:

  • Develop and implement process improvements for blown plastic film production, including extrusion, cooling, and winding processes.
  • Continuously monitor and assess manufacturing processes to increase efficiency, reduce waste, and enhance product quality.
  • Analyze production issues, including equipment failures, defects, and process inefficiencies.
  • Provide quick and effective solutions, collaborating with maintenance and production teams to minimize downtime.
  • Collect, analyze, and interpret data from production processes to identify trends and areas for improvement.
  • Prepare detailed reports on process performance, providing recommendations to management for optimization.
  • Ensure that equipment, including extruders, cooling units, and winders, are calibrated properly and operating within optimal specifications.
  • Lead troubleshooting efforts and coordinate with the maintenance team for equipment repairs and upgrades.
  • Develop and maintain standard operating procedures (SOPs), work instructions, and process control documents.
  • Ensure all documentation is up to date and accessible to the team for training and compliance purposes.
  • Work with production teams to identify areas where cost reductions can be achieved without sacrificing product quality.
  • Implement and monitor changes that lead to reduced material waste and energy consumption.
  • Collaborate with the quality assurance and production teams to implement process changes, conduct pilot runs, and ensure consistent product output in line with customer requirements.
  • Ensure manufacturing processes adhere to industry standards and regulations, including quality control systems.
  • Work closely with quality assurance teams to meet product specifications and resolve any deviations.

ESSENTIAL JOB DUTIES:

  • Process Improvement:
  • Lead efforts to enhance existing production processes, focusing on maximizing throughput, minimizing defects, and improving product consistency.
  • Monitor key performance indicators (KPIs) such as cycle time, material efficiency, and product quality.
  • Project Management:
  • Manage engineering projects, from initial design to final implementation, for process improvements and new equipment integration.
  • Ensure projects are completed on time, within budget, and meet all quality standards.
  • Technical Support and Troubleshooting:
  • Provide technical guidance during the operation of manufacturing processes, especially when problems arise, and support the resolution of process and equipment issues.
  • Work with the maintenance team to ensure the manufacturing equipment is maintained to prevent breakdowns.
  • Partner with operations to ensure that processes are followed and provide feedback to improve operational efficiency.
  • Quality Control and Testing:
  • Coordinate with quality control teams to ensure the films meet the required specifications, including thickness, clarity, strength, and other physical properties.
  • Participate in root cause analysis and corrective actions for any deviations from quality standards.
  • Cost Management:
  • Review process data and recommend solutions to optimize material usage, energy consumption, and labor efficiency to help control production costs.

SKILLS & ABILITIES:

  • In-depth knowledge of manufacturing processes, particularly in the blown film extrusion and winding processes.
  • Strong analytical and troubleshooting skills.
  • Strong attention to details.
  • Excellent written and verbal communication skills.
  • Proficiency in analyzing production data using tools like Microsoft Excel, ETP Systems, etc.

EDUCATION & EXPERIENCE:

  • Bachelor’s degree in manufacturing engineering or mechanical engineering required.
  • Minimum of 3-5 years’ experience in a manufacturing environment, preferably plastic films.
  • Proven experience in implementing process improvements, troubleshooting, and working in a high-volume manufacturing environment.
  • 1-2 years' experience with AutoCAD, AutoCAD LT, MATLAB, or Python.

PHYSICAL REQUIREMENTS:

  • Ability to stand or walk for prolonged periods of time.
  • Ability to lift up to 50lbs on your own.
  • Exposure to loud noise, fluctuating temperature, and dust.

Seniority level

  • Entry level

Employment type

  • Full-time

Job function

  • Engineering and Information Technology

Industries

  • Manufacturing

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.