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Senior niche ML role at Tier-1 Adobe in Bengaluru reduces applicant density despite strong brand and broad generative AI requirements.
Specialized generative AI and large-scale vision model expertise limits transferability outside ML/AI domains.
Explicit 15+ years, PhD/MS, mandatory diffusion/vision expertise and distributed training demands strict shortlisting.
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Architect, develop, and deploy large-scale diffusion-based generative models for image, video, and multimodal tasks.
Own full ML lifecycle including training infrastructure design, model optimization, deployment, and evaluation frameworks for generative AI.
Lead and mentor a team of ML engineers; set technical standards and collaborate cross-functionally to integrate research into production features.
15+ years of hands-on ML engineering experience in industry or research.
MS or PhD in Computer Science, Machine Learning, Statistics, or equivalent practical experience.
Expert-level Python and strong mandatory proficiency in PyTorch.
Deep knowledge of diffusion models, computer vision fundamentals, distributed training frameworks, and demonstrated track record of shipping ML models at scale.
Experienced senior-level applied scientist with extensive background in both generative modeling (diffusion, score-based) and computer vision domain.
Proven operator in building scalable, production-grade ML systems with distributed GPU infrastructure expertise.
Technical leader comfortable mentoring engineers and working cross-functionally to translate cutting-edge generative AI research into reliable, impact-driven software products.