Senior Machine Learning Engineer (Computer Vision)
Location: Berlin
Senior Machine Learning Engineer (Computer Vision)
Your Tasks:
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Lead model development for computer vision and 3D analysis tasks (e.g., object segmentation, surface classification, and geometry-based inference).
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Evaluate and integrate pre-trained models (e.g., vision transformers, segmentation networks, diffusion-based methods) to accelerate delivery.
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Train and fine-tune models on in-house and synthetic datasets.
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Deploy models to production in collaboration with MLOps and backend teams (Python-based stack, GCP infrastructure).
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Maintain and monitor production models, ensuring accuracy, performance, and reliability.
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Collaborate cross-functionally with software, product, and operations teams to translate product requirements into ML deliverables.
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Document and communicate findings, models, and pipelines.
Your Profile:
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5+ years of experience in applied Machine Learning, with at least 3 years in computer vision (e.g., image segmentation, detection, or reconstruction).
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Solid experience with PyTorch or TensorFlow, OpenCV, and Python.
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We are looking for a senior engineer willing to grow into the head of ML. You will report directly to CTO
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Strong understanding of CNNs, vision transformers, feature extraction, and 3D vision (SfM, MVS, or point clouds a plus).
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Experience with training pipelines, dataset management, and hyperparameter optimization.
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Familiarity with model deployment (FastAPI, Flask, TorchServe, Vertex AI or custom inference services).
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Experience with GCP or other cloud ML infrastructure, Docker, and CI/CD for ML pipelines.
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Comfortable reading academic papers, evaluating SOTA architectures, and adapting them to production constraints.
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Strong communication and documentation skills โ capable of maintaining project continuity during a temporary leadership gap.
Nice to Have:
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Experience with photogrammetry, geospatial data, or 3D reconstruction workflows.
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Familiarity with ML experiment tracking (Weights & Biases, MLflow).
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Experience with data annotation pipelines and semi-supervised learning.
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Contribution to open-source ML projects.
What We Offer:
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Opportunity to lead the AI roadmap in a high-impact domain (renewable energy and 3D mapping).
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Collaborative and pragmatic engineering culture โ focused on results, not meetings.
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Direct collaboration with the CTO and MLOps team.
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Flexible hybrid setup (Berlin-based)
Laura Kelm
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