Senior Computer Vision Engineer

About the role

Funstop Games is looking for a hands-on Senior Computer Vision Engineer to build, optimize and deploy advanced machine learning models for real-world applications. The role takes ownership of computer vision projects end to end, from dataset preparation and model training to evaluation, optimization and production deployment, while helping shape the AI architecture, setting engineering best practices and mentoring other engineers.

Key responsibilities

• Design, train, fine-tune and evaluate computer vision models for object detection, image classification and instance segmentation
• Benchmark CNN and transformer architectures, run error analysis and ablation studies, and improve model performance
• Improve inference speed, memory efficiency and computational performance, and prepare models for production with backend and infrastructure engineers
• Define dataset requirements, improve data quality, address class imbalance and bias, and set up evaluation and validation workflows
• Build reproducible pipelines, maintain clean and testable code, and establish versioning and best practices
• Mentor AI/ML engineers, review code, guide architecture and collaborate with product and engineering leadership

Required profile

• Bachelor's or Master's degree in Computer Science, AI, Machine Learning or a related field, or equivalent practical experience
• 5+ years of hands-on experience developing computer vision or applied deep learning systems
• Ability to solve complex technical problems independently and communicate effectively in English
• Preferred: mentoring experience, open-source contributions, publications or production ML projects

Required skills

• Strong Python and PyTorch; CNNs and Vision Transformers
• Evaluation metrics such as precision, recall, F1-score, IoU and mAP
• GPU training, model optimization and production inference
• Git and clean code practices
• Preferred: RF-DETR, RT-DETR, YOLO, Detectron2, MMDetection, ONNX Runtime, TensorRT, MLflow, Weights & Biases, DVC, cloud GPU infrastructure

To apply, send your CV and links to relevant projects, publications or GitHub repositories.