Senior Computer Vision Scientist
Location: Copenhagen, Denmark
Wind Power LAB has an exciting opportunity for a Senior Computer Vision Scientist to join the team, based in Copenhagen, Denmark.
About Wind Power LAB
Wind Power LAB is a specialized engineering and consulting company supporting the wind energy industry with expertise in blade technology, inspections, failure analysis, and root cause investigations. We work closely with global partners to improve the reliability and performance of wind turbine blades.
We are a small consultancy company with 11 employees and expect to grow quite significantly in the future.
Role Overview
As part of our technical team, you will build and maintain the internal tools that enable Wind Power Lab’s blade experts to work efficiently:
- Inspection workflow tools – Platforms for managing blade assessments, annotations, and client deliverables
- Data infrastructure – Systems that organize and process inspection data from projects across six continents
- Expert support – Continuous development and maintenance to keep blade engineers productive and responsive to client needs
As a Senior Computer Vision Scientist, you will own the end-to-end pipeline of industrial AI solutions. You will bridge the gap between academic innovation and production-ready systems, moving beyond standard CNNs to implement state-of-the-art architectures that solve “in-the-wild” inspection challenges.
What We Offer
You will have the unique opportunity to be a key player in making sure the company’s internal and external tools runs smoothly and maintained. You will also participate in the development of new tools.
- The chance to work in a high-growth international company with a strong brand
- Close collaboration with management and key stakeholders
- Short decision paths and a pragmatic approach to problem-solving
- Being part of a very inclusive team
- Reporting directly to the Head of Technology
Responsibilities
- Architect & Innovate: Design and train state-of-the-art models for segmentation, detection, and anomaly detection, moving from traditional CNNs to Vision Transformers (ViTs) and Attention-based architectures.
- Efficiency & Optimization: Apply Parameter-Efficient Fine-Tuning (PEFT) techniques, such as LoRA, to adapt large-scale models to specific industrial domains with limited data.
- Full Lifecycle Deployment: Own the transition from research to production using Docker and GCP, ensuring models are optimized for real-time inference and scalability.
- Data Engineering: Build sophisticated synthetic data and augmentation pipelines to ensure model robustness against environmental variability.
- Multimodal Integration: Explore the intersection of Vision and Language (Vision-Language Models) to improve automated diagnostics and report generation (NLP).
Qualifications:
- Academic Background: Master or PhD in a STEM field (Mathematics, Computer Science, or Engineering) plus industrial experience or an MSc with 5+ years of applied research experience.
- Industrial Research: Proven track record of taking theoretical research (Academic papers) and implementing it in an industrial setting.
- Proven Impact: Experience in the full lifecycle of a vision project: from raw data acquisition and dataset curation to deploying models that provide actionable business value.
Technical Skills
Core Machine Learning & Frameworks:
- Programming: Expert-level Python and familiarity with C++.
- Deep Learning: Expert-level PyTorch (preferred) or TensorFlow.
- Modern Architectures: Hands-on experience with Vision Transformers (ViTs), VAEs, and CNNs.
- Advanced Training: Proven expertise in Parameter-Efficient Fine-Tuning (LoRA/Adapter tuning) and Transfer Learning.
- Hugging Face Ecosystem: Proficiency in using the Hugging Face Hub, Transformers, and Diffusers libraries for rapid model prototyping and deployment.
Tools, MLOps & Infrastructure:
- Experiment Tracking: Deep experience with Weights & Biases (W&B) or MLflow for reproducibility and hyperparameter optimization.
- Production & DevOps: Proficiency in Docker for containerization and GCP/AWS/Azure for cloud-scale training and deployment.
- Computer Vision Libraries: Strong command of OpenCV for classical image processing and data augmentation, and experience with 3D reconstruction and geometric vision.
- High-Resolution Data: Experience working with large-scale, high-resolution datasets (like drone imagery) where data efficiency is critical.
- Statistical Inference: Ability to draw data-driven conclusions and use statistical methods to validate model performance.
- Developer Workflow: Expert use of GitHub (CI/CD, version control) and Linux/Bash environments.
Nice to Have:
- Mathematical Fundamentals: Solid understanding of optimization, statistical inference, and evaluation metrics for skewed industrial datasets.
- NLP & LLMs: Familiarity with Large Language Models and Natural Language Processing for structured data extraction or “Human-in-the-Loop” interfaces.
- Edge & Inference: Knowledge of model acceleration (TensorRT, ONNX) for deploying high-resolution vision models to edge devices.
- Published peer-reviewed papers on Computer Vision or Machine Learning (CVPR, WACV, ICML, etc).
Soft Skills:
- Self-Drive & Ambiguity: Ability to navigate unstructured problems and drive architecture innovation independently.
- Scientific Communication: Excellent English skills to translate complex ML solutions to stakeholders and domain experts.
- Collaborative Spirit: Comfortable working in small, horizontal teams where communication across different technical backgrounds is essential.
Deadline:
March 16th 2026
Employment Type:
Full-Time Role
Location:
Copenhagen, Denmark
Submit Your Application Here
If you are interested in joining the Wind Power LAB team, we would love to hear from you.
Interested candidates are invited to apply by email and include the following documents:
- CV
- Cover Letter
Please send your application to humanresources@windpowerlab.com
Application deadline: March 16, 2026, all applications will be evaluated on ongoing basis.