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Veo is a global leader in AI-based sports camera technology. Our innovative, fully automatic camera solution enables sports teams to record matches and training sessions without a camera operator. We’re democratizing the world of sports by granting video analysis for teams on all levels—a privilege that used to be only for the few. More than 50,000 clubs in 90+ countries record their games every week. Growing as fast as we do in Veo means that every day is different, exciting, and challenging, both on the front line and in the back office. But that’s not the most remarkable thing about us. The coolest thing is our people. We’ve attracted some of the brightest minds in the industry. They are the reason we can create a great product and do it while enjoying ourselves. As a Machine Learning Engineer at Veo you will get to work on challenging problems and directly contribute to the value created by our AI-driven end-user products. You will become part of our AI team, which comprises 15 researchers and engineers responsible for all stages in the machine learning lifecycles across different projects - from scoping and defining data annotation tasks to modeling, validation, and deployment. You will be free to determine the directions of the project you work on while also getting feedback and being encouraged to spar with the rest of the team to assist each other in improving and succeeding. We stay current with the latest research and continuously discuss concepts and ideas in recent papers to assess their relevance to our tasks and product-specific challenges. We are looking to add yet another ambitious, high-performing junior to senior engineer/researcher with proven experience from real-world machine learning projects to the team. Experience with computer vision is advantageous but not a must.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.