About Us

We are a cutting-edge technology company specializing in media forensics. Our mission is to develop advanced AI solutions that detect and localize tampering attempts in digital media such as images and PDFs, ensuring the authenticity and integrity of our clients' content. As part of our innovation roadmap, we are also exploring the integration of Large Language Models (LLMs) to enhance our detection capabilities.

The Role

As a Senior AI Researcher, you will lead the development of deep learning models for detecting and localizing tampering in images and PDFs. Your expertise in computer vision, AI model optimization, and GPU-accelerated computing will be instrumental in advancing our forensic technology. While the primary focus is on computer vision, experience with LLMs and NLP is a plus for candidates interested in contributing to broader AI research initiatives.

Responsabilities

Research & Development:

• Lead the design and optimization of deep learning models for tampering detection in images and PDFs.
• Develop algorithms that improve the accuracy, robustness, and interpretability of forensic models.
• Explore methods to enhance detection capabilities using multimodal AI approaches.

Performance Optimization:

• Optimize AI inference workloads on GPU clusters to ensure efficient processing of high-resolution media.
• Implement and maintain high-performance code using CUDA C++ and other GPU programming techniques (including SIMD and VLIW).

Computer Vision & Deep Learning:

• Work with the PyTorch ecosystem (TorchVision, TorchRL, TorchAudio) to build scalable and reliable AI models.
• Research and apply state-of-the-art computer vision techniques, including feature extraction, adversarial attack detection, and anomaly detection in media content.

Collaboration & Integration:

• Work closely with data engineers and software developers to integrate AI models into production pipelines.
• Assist in designing model evaluation frameworks to ensure high detection accuracy in real-world applications.

Optional – LLM Research & Integration:

• If applicable, explore how LLMs can enhance tampering detection and forensic analysis.
• Research and fine-tune LLMs for media forensics, leveraging domain-specific datasets.

Qualifications

Experience:

• Proven experience in developing computer vision models, particularly for image forensics, object detection, or anomaly detection.
• Strong background in deep learning, convolutional neural networks (CNNs), and image processing techniques.
• Experience optimizing AI inference workloads on GPU clusters.

Technical Expertise:

• Proficiency with the PyTorch ecosystem (TorchVision, TorchRL, TorchAudio).
• Strong understanding of image forensics, adversarial attack detection, or related fields.
• Experience with CUDA C++, SIMD, and VLIW for high-performance computing.
• (Optional) Familiarity with LLM fine-tuning and NLP-based AI applications.

Education:

• A Bachelor’s, Master’s degree or PHD in Computer Science, Electrical Engineering, AI, or a related field. Advanced degrees or equivalent research experience are a plus.

Soft Skills:

• Excellent analytical and problem-solving abilities.
• Strong communication skills and a collaborative mindset suited for a fast-paced research environment.

Why us?

If you work with us, you will have more control over your time and the opportunity to learn and experiment within a great team. As part of the selection process, you are encouraged to talk with as many team members as you want so you can learn more about us.

We offer

• Fully remote work
• Salary based on experience
• Coaching and learning opportunities
• Social virtual Fridays