Applied AI Engineer — Creative Cloud

About this Applied AI Engineer role at Adobe India

Adobe is hiring Applied AI Engineers in Bengaluru to build generative AI features powering Creative Cloud products like Firefly and Express. As a mid-level AI engineer, you'll work on production-grade diffusion models and multimodal systems at scale—this is a direct, permanent role at one of India's largest AI employers, with salary and equity reflecting senior IC expectations.

What you'll do

• Develop and optimize PyTorch-based diffusion models for generative creative features in Firefly and Express
• Design and train multimodal AI systems that understand both text and visual inputs
• Optimize model inference performance for production deployment across Creative Cloud applications
• Collaborate on end-to-end pipelines from research prototypes to user-facing generative features
• Contribute to core AI architecture decisions for Adobe's next-generation creative tools

Who should apply

You need a B.Tech or M.Tech degree and 4–8 years of hands-on AI experience, including at least some production deployment work. This is a mid-level Applied AI Engineer role—not entry-level, but not requiring 10+ years either. You should be comfortable with PyTorch, familiar with diffusion model concepts, and have shipped or debugged real ML systems. Strong background in deep learning and performance optimization is essential.

Salary & offer in context

Adobe offers ₹40–90 LPA plus RSUs for this Applied AI Engineer role in Bengaluru. At the mid-level, that translates to roughly ₹3.3–7.5 lakhs per month—well above typical Applied AI Engineer salary in India (which averages ₹20–50 LPA for mid-career roles). This reflects Adobe's scale and the seniority of generative AI work.

Path to apply

This is a direct apply role through Adobe's online careers portal—no exams, no multi-round screening gauntlet. Apply directly at careers.adobe.com and upload your resume, GitHub links, and any ML projects you've shipped. The application deadline is 7 June 2026, so apply soon if you meet the 4–8 years + PyTorch + production deployment criteria.