Senior Computer Vision Engineer
RemoteHungary
Job Summary
Build and improve deepfake and liveness detection models using CNNs, attention layers, and vision-language models. Design, train, and evaluate models end-to-end from data preparation to result checking, then fine-tune vision-language models with efficient methods like LoRA. Make models smaller and faster for cloud and on-device use by optimizing neural networks for deployment. Build and maintain training and deployment pipelines to ship models into production on AWS, while using AI-assisted coding tools to accelerate experimentation. Share progress clearly with technical and non-technical stakeholders and own independent R&D initiatives within the cross-functional Computer Vision team.
Required Qualifications
- A BSc, MSc or Ph.D. in engineering, computer science or a related field
- At least 5 years of professional experience developing and deploying deep learning and computer vision models
- Strong grasp of the end-to-end ML workflow: preparing data, training models and evaluating results
- Solid grounding in modern neural network architectures, including convolutional networks and attention mechanisms
- Working understanding of large language models (LLMs), vision-language models (VLMs) and adaptation techniques
- Strong communication skills, able to present work clearly to senior and non-technical stakeholders
- Experience working in agile environments, with strong analytical and problem-solving skills
- Expert-level Python, with proven experience building deep learning models in production
- Professional experience with modern deep learning frameworks such as PyTorch, TensorFlow or JAX
- Hands-on experience deploying and optimising models on AWS (e.g. EC2, Athena) and related MLOps services
- Experience optimising neural networks for deployment, including model compression, quantisation and runtime optimisation
- Fluent in Linux/Unix and comfortable with Docker and containerised workflows
- Day-to-day use of AI-assisted coding tools such as Claude Code
Desired Qualifications
- Experience with deepfake detection, face anti-spoofing / liveness, biometric security or media forensics is a strong plus
- Experience leading or mentoring machine learning engineers is a strong plus
- Familiarity with C++ is a plus
- Knowledge of GPU-based / distributed training and mobile deployment is a strong plus
- Experience with AWS SageMaker is a plus
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