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Senior Computer Vision Engineer (m/f/d)

External
deltia logoDeltia · Berlin, Germany
Full-timeOn-site13mo ago
AirflowAWSCI/CDComputer VisionDockerEmbedded Systems
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Requirements

  • Experience deploying CV models on edge devices or embedded systems
  • Familiarity with TensorRT, quantisation, and real-time inference optimisation
  • Background in video analytics, action recognition or multi-modal perception
  • Understanding of model orchestration frameworks and large data pipelines
  • Why this role matters
  • You bridge research and production - turning cutting-edge computer vision models into robust, real-time systems that power intelligent industrial automation.

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're looking for a Computer Vision Engineer focused on bringing advanced vision models into production. You'll own the full lifecycle of CV systems - from model integration and orchestration to deployment on cloud and edge environments. Your role Develop and deploy computer vision models for real-world video and sensor applications Build reliable training, evaluation and inference pipelines for large-scale data Operate and optimise GPU clusters, Docker/Kubernetes environments and cloud workloads Implement CI/CD, versioning and orchestration for ML pipelines Collaborate with research engineers to transition prototypes into scalable, production-grade systems Work with robotics and platform teams to ensure robust deployment at the edge You are 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

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