Clarity is an AI cybersecurity startup, protecting against deepfakes and new social engineering and phishing attack vectors accelerated by the rapid adoption of Generative AI. Its patent-pending technology detects AI manipulations in videos, images and audio and authenticates media with encrypted watermarking. Clarity's AI DeepFake Firewall integrates into new and existing workflows, and enables publishers and intelligence agencies to verify sensitive media, financial institutions to prevent fraud, and enterprises to filter manipulated media and create an AI-Safe media environment — in a market that's growing at ~40% CAGR. Founded by AI and Cyber experts from 8200, Stanford, and Israel’s National Security Council, it is advised and backed by global leaders in the AI and cyber industries.

We are looking for an experienced AI Researcher with expertise in Computer Vision to join our dynamic team. As a pivotal member, you will contribute to cutting-edge research and development of our synthetic (deep fake) detection tools as well as the our overall AI products. This position presents an exciting opportunity to work on innovative projects at the intersection of artificial intelligence computer vision and many other existing fields.

Responsibilities

• Research and develop existing and new AI computer vision algorithms particularly in the fields of synthetic detection, staying abreast of the latest developments and emerging trends
• Design and build (together with the ML Engineering team) pipelines for media information preprocessing to facilitate model training
• Integrate, test, assess and improve deployed algorithms within the company systems
• Collaborate closely with Machine Learning Engineers, Software Developers, and domain experts to understand project requirements and achieve objectives

Requirements

• 3+ years track record of research and development of AI algorithms with expertise in computer vision applications, related to facial video or image processing, generative AI or other related fields
• PhD or Masters in Compute Science Mathematics or Engineering
• Experience with designing ML software solutions with a focus on deep learning, including proficiency in designing scalable and maintainable ML systems, implementing algorithms, and optimizing code for performance
• Proficiency in python programming languages or equivalent
• Experience with deep learning frameworks, such as PyTorch or TensorFlow
• Experienced with CV tools - OpenCV, Scikit-Image, Scikit-Video
• Strong teamwork skills and ability to collaborate and communicate effectively

Benefits

• Experience with other domain of AI like Forgery or Outlier Detection
• Additional coding proficiency