Senior Computer Vision Engineer

Realeyes - Vision AI

Senior Computer Vision Engineer developing deepfake and liveness detection models with a cross-functional R&D team in Hungary. Working on a large-scale facial and video database to ensure system integrity and authenticity.

Posted 7/4/2026full-timeRemote • 🇭🇺 HungarySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying deep learning and computer vision models, with a strong focus on end-to-end machine learning workflows and optimization techniques for production environments. Proficient in using modern deep learning frameworks and cloud services to enhance model performance and efficiency.

Highest-signal resume keywords

Deep Learning Model DevelopmentComputer Vision ExpertiseAWS Deployment and OptimizationPython ProgrammingModel Compression and Quantization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Convolutional Neural NetworksAttention MechanismsVision-Language ModelsMachine Learning WorkflowModel EvaluationDeepfake DetectionBiometric SecurityPyTorchTensorFlowJAX

Soft Skills

Analytical SkillsProblem-SolvingCommunication

Tools & Technologies

AWS EC2AWS AthenaMLFlowClaude Code

Industry Keywords

Liveness DetectionFace Anti-SpoofingMedia ForensicsAgile Environments

Tech Stack

Tools & technologies

AWSCloudEC2PythonPyTorchTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.
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.
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.

Benefits

Comp & perks

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