- Company Name
- IDEMIA
- Job Title
- Research/AI Engineering 1
- Job Description
-
**Job Title**
Research/AI Engineer – Deepfake Detection 1
**Role Summary**
Develop, optimize, and deploy cutting‑edge deepfake detection algorithms to secure biometric systems. Conduct end‑to‑end research from data collection to model training, benchmarking, and publication, while integrating solutions across cloud, on‑premises, embedded, and mobile platforms.
**Expectations**
- Deliver novel, high‑performance detection models that outperform current benchmarks.
- Translate research findings into production‑grade systems and provide technical guidance to operations teams.
- Continuously monitor scientific literature and emerging techniques to keep the defense stack state‑of‑the‑art.
- Collaborate cross‑functionally, communicate results clearly to technical and non‑technical stakeholders, and contribute to research publications or patents.
**Key Responsibilities**
1. Design and prototype innovative algorithms (CNN, Transformer, GAN, Diffusion, VLM, Bayesian methods) for deepfake detection.
2. Optimize models for speed, memory, and accuracy across diverse deployment environments.
3. Collect, curate, and preprocess large image/video datasets; perform feature engineering and data augmentation.
4. Evaluate models using rigorous metrics; conduct ablation studies and benchmark against state‑of‑the‑art techniques.
5. Perform technical literature reviews; synthesize findings into actionable research roadmaps.
6. Work with operations teams to translate research prototypes into robust, scalable solutions for specific client needs.
7. Integrate solutions into cloud services, embedded devices, or smartphones, ensuring compliance with security and performance requirements.
8. Document research methodology, results, and model specifications; author papers, technical reports, or patent submissions.
9. Mentor junior researchers or interns as needed.
**Required Skills**
- Strong background in computer vision and deep learning; experience with CNNs, Transformers, GANs, Diffusion models, and Vision‑Language Models.
- Proficiency in Python, PyTorch (or equivalent), and C/C++; ability to process and scale large datasets.
- Solid knowledge of Bayesian inference, statistical learning, and data analysis.
- Familiarity with biometrics or document analysis is a plus.
- Excellent problem‑solving, autonomous work style, and curiosity-driven mindset.
- Clear written and verbal communication in English; additional language skills welcomed.
**Required Education & Certifications**
- Ph.D. or Master’s degree (or equivalent) in Computer Science, Electrical Engineering, Data Science, or a related field; thesis or substantial research project required.
- Professional certifications are not mandatory.
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