- Fine-tune diffusion models to enhance image quality, resolution, and style adaptability.
- Optimize prompt engineering techniques to refine and control image generation outputs.
- Develop post-processing and ranking algorithms to improve the accuracy and aesthetics of generated images.
- Integrate diffusion models with other AI techniques, including GANs, transformers, and hypernetworks, to expand generative capabilities.
- Deploy AI models into production environments, ensuring scalability and efficiency.
- Utilize containerization tools (Docker, Kubernetes, etc.) to streamline AI model deployment.
- Collaborate with AI researchers and product teams to bring AI-powered image generation solutions into real-world applications.
- BTech/MTech/MS in Computer Science, AI, or a related field.
- 2+ years of experience working with Generative AI and Computer Vision.
- Strong expertise in diffusion models, generative AI, and image processing.




- Hands-on experience with model fine-tuning and optimization.
- Understanding of ControlNets, hypernetworks, and AI-based prompt engineering.
- Proven track record in AI model deployment and scalable pipelines.
- Experience working with production-grade AI workflows and cloud-based solutions.
- Strong debugging skills – Ability to troubleshoot model failures and optimize performance.
- Team player mindset – Comfortable working with cross-functional teams.
- Excellent communication & presentation skills – Ability to explain research concepts clearly.
- Comfortable working in a high-performance, in-office workplace.
- Takes ownership from Day 1, proactively solving challenges.

Skills: Docker, Kubernetes, Computer Vision, Transformers

Experience: 2.00-5.00 Years

📌 Computer Vision (GEN AI) (Gurugram)
🏢 Spyne
📍 Gurugram