I’m a native Frenchin computer vision in Japan and later in my home country. Yet, I’m writing from an unlikely computer vision hub: Stuttgart, Germany.
But I’m not working on German car technology, as expected. Instead, I found an incredible opportunity mid-pandemic in one of the most unexpected places: An e-commerce-focused, AI-driven, image-editingthe digital imaging process across all retail products.
My experience in Japan taught me the difficulty of moving to afor work. In Japan, having a point of entry with a professional network can often be necessary. However, Europe has an advantage here thanks to its many accessible cities. Cities like Paris, London, and Berlin often offer diverse job opportunities while being hubs for some specialties.
While there has been an uptick in fully remote jobs thanks to the pandemic, extending the scope of your job search will provide more opportunities that match your interest.
Search for value in unlikely places, like retail.
I’m working at the technology spin-off of a luxury retailer, applying my expertise to product images.scientist’s point of view, I immediately recognized the value of a novel application for a vast and established industry like retail.
Europe has some of the most storied retail brands in the world — especially for apparel and footwear. That rich experience provides an opportunity to work with billions of products and trillions of dollars in revenue to which imaging technology can be applied. The advantage of retail companies is a constant flow of images to process, providing a playing ground to generate revenue and possibly make an AI company profitable.
Another potential avenue to explore is independent. I found many AI startups working on a segment that isn’t profitable simply due to the cost of research and the from very niche clients.
Companies with data are companies with revenue potential
I was particularly attracted to this startup because of the potential. work with a finite set. Look for companies that directly engage at the B2B or B2C level, especially retail or digital platforms that affect the front-end .
Leveraging such customer engagement data benefits everyone. You can apply it towards furtheron other solutions within the category, and your company can then work with different verticals on solving their pain points.
I advise looking for companies with data already stored in a. Such a system will be beneficial for research and development. It also means there’s massive potential for revenue gains the more cross-segments of an audience the brand affects.
The challenge is that manyintroduced such a system, or they don’t have someone to utilize it properly. If you find a deep insights during the courtship processor hasn’t implemented it, look at the opportunity to introduce such data-focused offerings.
In Europe, the best bets involve creating automation processes.
I have a sweet spot for early-stage companies thatprocesses and core systems. The company I work for was still in its when I started, and it was working towards creating scalable technology for a specific industry. The questions the team was tasked with solving were already being solved, but numerous processes still had to be put into place to solve many other issues.
Our year-long efforts to automate bulk image editing taught me that as long as the AI you’re building learns to run independently across multiple variables simultaneously (multiple images and workflows), you’re developing a technology that does whathaven’t been able to do. In Europe, very few companies are doing this, and they are hungry for talent who can.
So don’t be afraid of a bit of culture shock and leap.