Automation Engineering Manager

Tesco
Welwyn Garden City
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager

Machine Learning Manager, London

AI Project Manager

PowerApps Developer (Engineering, Construction)

Manager Data Engineer - D&ET - Technology Consulting - Belfast & Derry/Londonderry

Data Engineer/Technologist Intern

Automation Engineering Manager

Direct message the job poster from Tesco.

About The Role

At Tesco, we believe in the power of spending more time together, face to face, than apart. So, during your working week, you can expect to spend 60% of your time in one of our office locations or local sites and the rest remotely. We also recognise that life looks a little different for each of us. Some people are at the start of their careers, some want the freedom to do the things they love. Others are going through life-changing moments like becoming a carer, nearing retirement, adapting to parenthood, or something else. That’s why at Tesco, we always welcome a conversation about flexible working. So, please talk to the Hiring Manager about how they can support you.

Are you ready to be part of a diverse team that collaborates to deliver outstanding customer experiences? Tesco Property Maintenance are looking for hardworking and efficient Maintenance Technicians to join our growing Property Maintenance Team! At Tesco, our stores and offices couldn’t function without the support of our integral teams.

You will be responsible for:

  • Understanding how technology is key to the future of Tesco, making sure automation is at the heart of our decisions.
  • Benchmarking across the industry to include best practices and drive continuous improvement.
  • Establishing and maintaining system development standards.
  • Combining technologies building blocks like image-based modeling, AI and machine learning, and physics-based modeling optimising the customer experience and value.
  • Identifying, scoping, and developing plans and new capabilities to use across the Network.
  • Developing and integrating network-wide technology building blocks for projects.
  • Interpreting information to measure the anticipated outcome of decisions, describing the typical tasks associated with using and managing suppliers, and understanding issues and considerations for inbound and outbound processes.
  • Engaging with relevant subject matter experts, leading and motivating them to contribute to the delivery of the project.
  • Taking ownership of processes and systems, ensuring they are effective and efficient; spotting issues and swiftly finding the best simplest solutions.
  • Managing interdependencies and any potential conflicts, working with others to deliver the objectives/scope and for the good of customers, colleagues & planet.
  • Managing risk and issues, setting up and leading a clear governance programme.
  • Advising on a variety of financial tools, techniques, and approaches and helping build cases.
  • Monitoring progress of delivery and updating stakeholders including business leaders on the deliverables.

You will need:

  • Analytical and critical thinking.
  • Attention to detail and finance awareness.
  • Qualifications in mechanical engineering or mechanical engineering technologies.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

Retail

#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.

Jobs

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!

Jobs Careers

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.