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Computer Vision Engineering - Talent Pool

External
deltia logoDeltia · Berlin, Germany
Full-timeOn-site6mo ago
AirflowAWSComputer VisionDockerKubernetesMLOps
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Benefits

Employee Share Options Program for all permanent employees*An increasing benefits list: currently includes Urban Sports club and quarterly team retreats.Be on the forefront in defining what artificial intelligence means in manufacturingGain hands-on experience in working in an AI-first software companySupportive and inclusive culture that values diversity and promotes the advancement of underrepresented groups within the companyCollaborate with a diverse (currently more than 10 nationalities) and talented team, working on cutting-edge projects with real-world impactNetwork with professionals and leaders in the field, opening doors to potential future career opportunitiesWe have a very flat hierarchy, open 360° feedback, and flexible working hoursEthics⚖: We are committed to developing ethical AI softwareDon't meet all the requirements?*Only full-time, permanent roles are eligible for stock options. Part-time roles, contract roles, work-student, internships and freelance roles are not eligible for stock options.Vision insuranceFlexible scheduleEquity / stock options

Additional Information

We believe the best work happens when people are excited about what they're building and understand how their expertise creates real impact. Instead of the traditional "one-size-fits-all" application process, we're asking you to be deliberate about where you want to make your mark. This approach helps us understand your strengths upfront and ensures you're matched with work that energizes you. You'll know from day one what challenges you're tackling and how your contributions move the needle for our customers. By selecting your focus areas and attaching your CV, you're not just applying for a job, you're proposing how you want to shape the future of industrial computer vision with us. General guidelines 5-7 years experience in computer vision, ML engineering or production AI systems Strong in Python, PyTorch and modern CV architectures (e.g. temporal transformers, detection, tracking) Experienced with containerisation and orchestration (Docker, Kubernetes, MLFlow, Airflow, etc.) Familiar with distributed training, GPU management and inference optimisation Solid understanding of cloud infrastructure (AWS or similar) and MLOps tooling Pragmatic engineer - focused on reliability, reproducibility and maintainability You can now pick your areas in the Application form ->

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