As a Senior Computer Vision Engineer, you’ll work with one of the world’s largest facial and video databases to build deepfake and liveness detection models that safeguard the integrity and authenticity of world class systems at scale. You will apply the latest advances in deep learning — from convolutional networks to attention-based and vision-language models — and own models end to end: designing, training, optimising for size and speed, and shipping them to production through robust, automated pipelines. You will work within a cross-functional Computer Vision team, collaborating closely with researchers, ML Ops engineers and product team to shape both the science and the engineering of our core technology stack. Responsibilities: Build and improve our deepfake and liveness detection models using CNNs, attention layers and vision-language models. Design, train and evaluate models end to end, from preparing data to checking results, following good engineering practices. Fine-tune vision-language models using efficient methods such as LoRA. Make models smaller and faster for both cloud and on-device / mobile use. Build and maintain training and deployment pipelines to get models into production on AWS (e.g. EC2, Athena). Use AI-assisted coding tools such as Claude Code to speed up experimentation and prototyping. Share progress clearly with technical and non-technical colleagues, and own independent research & development initiatives. Qualification requirements: 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. 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. Technical requirements: Expert-level Python, with proven experience building deep learning models in production. Familiarity with C++ is a plus. 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. (MLFlow etc) 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. Knowledge of GPU-based / distributed training and mobile deployment is a strong plus. Experience with AWS SageMaker is a plus. What we offer: Opportunity to work in a young but well-established international company where what you do has a direct and immediate impact Unlimited paid holidays Life insurance and 100% paid sick leave Working from home setup Innovative employee recognition and reward system, Bonusly Strong benefit package including subsidized gym membership / sport allowance, online and offline team-building events, flexible working hours