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🤖 Machine Learning Engineer – Computer Vision & Generative AI – 100% 📍 Berlin, Germany | 💰 €50,000 - €70,000 + Benefits | 🌍 Hybrid Working Our client is a technology-driven organisation developing intelligent software solutions that leverage artificial intelligence, automation, and advanced data processing to solve complex business challenges at scale. Operating at the intersection of machine learning, software engineering, and product innovation, they are investing heavily in next-generation AI capabilities and expanding their engineering team to support the continued evolution of their platform and services. This role is ideal for a Machine Learning Engineer who enjoys taking cutting-edge AI solutions from research to production and wants to work on technically challenging projects with tangible real-world impact. ⚙️ Tech Stack: Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows 🚀 About the Role: As a Machine Learning Engineer, you will: Develop, train, and optimise machine learning models focused on computer vision and generative AI applications Build and deploy scalable ML solutions into production environments Design automation solutions that reduce manual effort and improve operational efficiency Monitor model performance, identify improvement opportunities, and enhance reliability and accuracy Collaborate closely with engineering, product, and operational teams to deliver practical AI-driven solutions Research emerging technologies and rapidly evaluate their suitability for business applications Contribute to the evolution of production-grade machine learning infrastructure and workflows ➕ Nice to Have: Several years of hands-on experience within machine learning and computer vision Strong Python development skills with experience using frameworks such as PyTorch or TensorFlow Practical experience working with generative AI technologies including diffusion models and GANs Understanding of ML deployment, scalability, performance optimisation, and production environments Experience with Docker and cloud-based infrastructure Knowledge of creative AI tools and visual content workflows Experience working with image-based products, digital content platforms, or related industries Strong analytical thinking combined with a pragmatic, solution-oriented mindset Ability to communicate effectively in an international and cross-functional environment 💪 Benefits: Opportunity to work on cutting-edge AI and machine learning technologies Highly collaborative and innovative working environment Flexible working arrangements with hybrid options Exposure to challenging technical problems with real-world impact Professional development support, training, and continuous learning opportunities Modern working environment with strong team culture and regular social activities ✉️ Due to the volume of applications, we may not be able to respond to everyone individually. However, we genuinely appreciate every application and will contact shortlisted candidates directly.
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.