Computer Vision Engineer

• 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 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.

See all jobs on JobTailor

Senior Computer Vision Engineer