AI Engineer

At Rapifuzz®, we're dedicated to our mission of ‘making security simple,’ and empowering organizations against the ever-evolving landscape of digital threats. Our core motivation revolves around securing digital environments and safeguarding sensitive data. Upholding values of integrity, innovation, collaboration, and customer-centricity, we strive to offer unparalleled cybersecurity solutions tailored to meet the unique needs of our clients.Who We Are? As an innovator in the cybersecurity domain, we take pride in our diverse portfolio of next-gen cybersecurity products and services designed to tackle a wide array of security challenges. Our team comprises seasoned cybersecurity professionals with extensive industry experience and deep domain knowledge. 

About the Role

We are seeking talented AI/ML Engineers to build end-to-end ML capabilities for processing images, video, audio, and multimodal data. You will handle preprocessing, model development, feature engineering, evaluation, explainability, and seamless integration with backend APIs and pipelines. Own the full ML lifecycle—from data ingestion to production deployment—ensuring scalability, robustness, and real-world performance across diverse applications.

Qualification

• Bachelor's or master's degree in computer science, Artificial Intelligence / Machine Learning, Data Science, or a related technical field
• 3-5 years of relevant industry or research experience in computer vision, media AI, or applied ML systems

Required Skills

• Design, create, and preprocess custom datasets from scratch, including collection, cleaning, augmentation, and labeling for AI tasks
• Build, train, and fine-tune ML/LLM models.
• Conduct experiments, hyperparameter tuning, ablation studies, and rigorous model evaluation.
• Optimize models for inference (e.g., quantization, distillation) and deploy via Docker, Kubernetes, or cloud platforms.
• Develop and expose ML models through APIs, collaborating with backend teams for integration into production applications with scalability, reliability, and monitoring.
• Track AI trends, prototype solutions, contribute to open-source projects, and document findings.

Preferred Skills

• Experience with real-time video processing pipelines, FFmpeg, edge deployment, or GPU optimization
• Hands-on experience with VAEs, diffusion models, and advanced generative architectures
• Transformer-based fusion for vision-language-audio tasks
• Experience integrating ML solutions into cybersecurity systems while meeting SLA and performance requirements
• Knowledge of scalable ML serving, cloud infrastructure, and distributed inference systems
• Demonstrated research and technical writing skills, including publication of at least one recent paper in Computer Vision, AI security, or a related field

Key Responsibilities:

• Design, create, and preprocess custom datasets from scratch, including data collection, cleaning, augmentation, and labeling for diverse AI tasks (e.g., NLP, computer vision)
• Build, train, and fine-tune LLM models using frameworks like PyTorch, TensorFlow, or JAX,.
• Conduct experiments, hyperparameter tuning, ablation studies, and model evaluation to advance research objectives .
• Optimize inference (quantization, distillation) and deploy via Docker/K8s/cloud (SageMaker/Vertex AI).
• Collaborate with cross-functional teams to integrate ML models into production applications, ensuring scalability, reliability, and monitoring.
• Track AI trends, prototype ideas, and contribute to papers/open-source.

Model Development & Multimodal Research

• Build and train deep learning models for detecting manipulated media (image/video/audio) using CNNs, Transformers, and multimodal architectures.
• Implement baseline detectors for:
  • Deepfake image/video detection
  • Lip-sync mismatch detection
  • Face Swap Detection
  • Spatio-Temporal Analysis
  • Illumination and Shading Analysis
  • Voice cloning detection / audio anomaly detection
• Develop multimodal fusion pipelines (simple concatenation → classifier).

Preprocessing & Data Engineering

• Implement preprocessing for image, video, and audio (frame extraction, spectrograms, MFCCs, lip landmarks).
• Handle multimodal alignment (audio-video synchronization).

Productionization

• Collaborate with backend engineers to expose ML models through APIs.
• Optimize models for:
  • Real-time inference
  • Scalability
  • Security & adversarial robustness

Soft Skills

• Ownership-driven mindset; ability to independently deliver ML components.
• Excellent communication, structured problem solving.