Atna.ai is seeking a self-directed R&D; AI Engineer with 2-3 years of dedicated, hands-on experience manipulating foundation models. In this role, you will take ownership of our synthetic media detection initiatives, dissecting state-of-the-art neural network architectures and customizing their underlying components to solve complex classification and segmentation challenges. As an independent researcher and solo contributor, you will bridge the gap between cutting-edge theoretical research and scalable, real-world deployment.
About the Role
In this role, you will take ownership of our synthetic media detection initiatives, dissecting state-of-the-art neural network architectures and customizing their underlying components to solve complex classification and segmentation challenges.
Responsibilities
- Architect, modify, and fine-tune foundation models for deepfake image detection, image-to-image edit segmentation, and complex video/audio manipulation analysis.
- Deconstruct and rebuild core architectural components—specifically Transformer encoders/decoders,
multi-head attention blocks, and latent space embeddings—rather than relying on out-of-the-box API implementations.
- Implement and iterate upon CLIP-based multimodal models, Vision Transformers (ViT), and advanced U-Net architectures for cross-modal forensic analysis and high-precision spatial segmentation.
- Engineer specialized loss functions (e.g., combined BCE + Dice, contrastive loss) and optimize gradient flows to achieve subpixel boundary accuracy in synthetic media detection.
- Refactor experimental PyTorch research code into highly optimized, production-ready Python pipelines, ensuring strict dependency management and CPU/GPU inference optimization.
- Containerize AI microservices using Docker and manage seamless deployments across multi-node Swarm clusters utilizing GitHub Actions CI/CD pipelines.
Qualifications
- Experience: 3-5 years of applied experience specifically training,
📌 Artificial Intelligence Engineer (New Delhi)
🏢 Atna.ai
📍 New Delhi
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