About the Job

About the Company

Our client is a pioneering security platform offering comprehensive deepfake detection. The company is a Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and is backed by DCVC. Their proactive deepfake and AI-generated content detection technology is developed by a leadership team with over 20 years of experience in applied research at the intersection of machine learning, data science, and cybersecurity.

With models defending against present and future fabrication techniques, the company is the best way to detect and deter fraudulent text, audio, and visual content, partnering with government agencies and enterprise clients to enhance security and detect fraud.

Role and Responsibilities

• Construct and maintain datasets to support the AI team's work, focusing particularly on computer vision (both image and video).
• Execute data generation, data cleaning, annotation, and new dataset construction.
• Help develop auto-annotation workflows for image and video data (e.g., identifying accessories such as hats, glasses, etc., in images of people).
• Collaborate with third parties to create new datasets (e.g., crowdsourcing images/videos) and annotate existing data.

About You

• 5+ years of software/data science/ML industry experience.
• Strong understanding of traditional vision processing techniques.
• 2+ years of implementing traditional vision processing techniques.
• Preferred: Bachelor's degree in STEM (science, tech, engineering, math).
• Proficient with Python.
• Experience working with large computer vision datasets (10M+ items).
• Familiarity with ML and deep learning theory (can be self-taught).
• Experience implementing ML and deep learning algorithms from the literature.
• Nice to have: Experience with perceptual hashing and image deduplication.

This job description has been tailored to ensure confidentiality for our client while retaining all essential details about the role and responsibilities.

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