Senior Machine Learning Engineer (Computer Vision)

Your Tasks:

• Lead model development for computer vision and 3D analysis tasks (e.g., object segmentation, surface classification, and geometry-based inference).

• Evaluate and integrate pre-trained models (e.g., vision transformers, segmentation networks, diffusion-based methods) to accelerate delivery.

• Train and fine-tune models on in-house and synthetic datasets.

• Deploy models to production in collaboration with MLOps and backend teams (Python-based stack, GCP infrastructure).

• Maintain and monitor production models, ensuring accuracy, performance, and reliability.

• Collaborate cross-functionally with software, product, and operations teams to translate product requirements into ML deliverables.

• Document and communicate findings, models, and pipelines.

Your Profile:

• 5+ years of experience in applied Machine Learning, with at least 3 years in computer vision (e.g., image segmentation, detection, or reconstruction).

• Solid experience with PyTorch or TensorFlow, OpenCV, and Python.

• We are looking for a senior engineer willing to grow into the head of ML. You will report directly to CTO

• Strong understanding of CNNs, vision transformers, feature extraction, and 3D vision (SfM, MVS, or point clouds a plus).

• Experience with training pipelines, dataset management, and hyperparameter optimization.

• Familiarity with model deployment (FastAPI, Flask, TorchServe, Vertex AI or custom inference services).

• Experience with GCP or other cloud ML infrastructure, Docker, and CI/CD for ML pipelines.

• Comfortable reading academic papers, evaluating SOTA architectures, and adapting them to production constraints.

• Strong communication and documentation skills — capable of maintaining project continuity during a temporary leadership gap.

Nice to Have:

• Experience with photogrammetry, geospatial data, or 3D reconstruction workflows.

• Familiarity with ML experiment tracking (Weights & Biases, MLflow).

• Experience with data annotation pipelines and semi-supervised learning.

• Contribution to open-source ML projects.

What We Offer:

• Opportunity to lead the AI roadmap in a high-impact domain (renewable energy and 3D mapping).

• Collaborative and pragmatic engineering culture — focused on results, not meetings.

• Direct collaboration with the CTO and MLOps team.

• Flexible hybrid setup (Berlin-based)