cyberette.ai

Data Lab Scientist – Computer Vision

About Cyberette

Cyberette is an AI-native cybersecurity company developing forensic-grade technology to

detect digital manipulation in video, audio, and images. Our mission is to restore trust in

digital communication and protect organizations from deception in the AI era.

About the Role

We’re looking for a Data Lab Specialist with a solid background in data operations and

computer vision. You’ll be responsible for building and maintaining high-quality datasets that

fuel our detection models, ensuring accuracy, diversity, and consistency across all data

pipelines.

This role combines hands-on technical work with coordination — ideal for someone who

enjoys both creating structure and collaborating across teams.

Key Responsibilities

• Curate, collect, and annotate large-scale datasets for image and video analysis.

• Collaborate with the AI team to align data preparation with model goals.

• Ensure quality control and consistency across all dataset sources.

• Guide and coordinate junior team members or interns working on data tasks.

• Perform exploratory data analysis and identify dataset gaps or biases.

• Maintain clear documentation and versioning of data pipelines.

Requirements

• BSc/MSc in Computer Vision, Data Science, or related field.

• Proven experience with dataset preparation and management for machine learning.

• Strong understanding of computer vision principles and data labeling workflows.

• Proficiency in Python, Pandas and/or Polars, NumPy, and OpenCV.

• Experience working collaboratively with ML or research teams.

• Highly organized, detail-oriented, and dependable.

What We Value

Cyberette is built by a team of people who care deeply about purpose-driven innovation. We

believe in using AI to protect truth, identity, and digital integrity — and data is the foundation

of that mission.

Bonus Skills

• Familiarity with dataset tools (Label Studio, CVAT, Supervisely).

• Knowledge of multimodal or synthetic data generation.

• Understanding of ethical AI and dataset governance principles