Senior Machine Learning Engineer (Computer Vision)

About Us

At Airteam Aerial Intelligence, we build cutting-edge solutions for drone-based 3D photogrammetry, solar planning, and automated data analysis.
Our platform combines 3D reconstruction, geospatial analytics, and computer vision to deliver precise and scalable insights to the renewable energy industry.

We’re looking for a Senior Machine Learning Engineer (Computer Vision) to join our AI team. You’ll take ownership of our model lifecycle — from exploration and experimentation to production integration — ensuring the continued delivery of high-quality AI features to our customers.

• 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.

• 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.

• 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.

• Flexible hybrid/remote setup (Berlin-based or EU-friendly timezone).
• 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.

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.
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• Contribution to open-source ML projects.