Senior iOS Mobile Software Engineer (ShelfView)

Scandit
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Research Engineer

Senior Data Scientist

Senior Data Scientist

Senior Machine Learning Scientist

Senior Data Scientist

Senior Data Scientist

*Please note we are only able to consider candidates based in (or willing to relocate to) Finland, Poland, Italy, Germany, and the UK.*

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows. It provides actionable insights to help businesses in a variety of industries. Join us as we continue to expand, grow, innovate, and help take Scandit to the next level.

Our newest product is called ShelfView and is a platform that lets retailers track the status of the shelves in their stores. For example, it helps them find products that are placed in the wrong spot, labeled with the wrong price or simply out of stock. ShelfView works with images captured from mobile or ceiling-mounted cameras, processes them with our computer vision and machine learning algorithms and provides actionable insights to retail store employees. For more information, please check our product website. 

To expand our Engineering team, we are now looking for a Senior iOS Software Engineer.

About the role 

You will be responsible for the ShelfView Capture App. The Capture App and the related SDK enable ShelfView users to use the mobile phone camera to capture retail shelves in an efficient and intuitive manner. This product is still under substantial development and new features and improvements will have a direct impact on the users. As a Senior iOS Software Engineer, you will play an instrumental role in architecting and implementing features, improving the stability and reliability, and working with stakeholders on defining and shaping the future of how users can capture in-store data and optimize retail operations.

Who you are

You are proficient with Swift / SwiftUI and know your way around the iOS universe You have experience with ARKit and ideally have knowledge of 3D representation methods You appreciate good software architecture and love to apply it to your code You have a track record of creating beautiful, engaging user experiences on iOS You are thorough and pay attention to detail You love to collaborate in a small and international team and quickly iterate on feedback. If required, you can take a leading role and own the delivery of features or projects.  You are willing to go beyond your role, your team and (sometimes) your comfort zone to make a cross-functional impact on the business

What We Offer

Here are just some of the reasons why people choose to build their career at Scandit: 

A highly skilled team and a fun environment where you can put your enthusiasm for cutting-edge technologies to use Excellent office infrastructure, optimized for hybrid working in Zurich, Warsaw, Tampere, and London. Excellent support for remote work across the UK, Italy and Germany Innovation hackathons  People-first culture Global team outings Your birthday off  An attractive individual equity plan in a high growth company  Specific benefits related to the location you are joining

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.