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Strong Tier-1 brand but senior, niche generative-ML profile reduces competition.
Requires deep generative ML and computer-vision expertise, limiting cross-industry transferability.
Explicit 15+ years, advanced degree expectation, and mandatory deep ML and distributed-training skills make screening strict.
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Architect and deliver state-of-the-art diffusion-based generative AI models for image, video, and multimodal tasks.
Own the full machine learning lifecycle including data curation, training, optimization, deployment, and monitoring at scale on distributed GPU infrastructure.
Lead and mentor engineering teams while collaborating cross-functionally to transition cutting-edge research into production-ready AI systems.
15+ years 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 mandatory proficiency in PyTorch.
Strong practical and theoretical expertise in diffusion models and computer vision fundamentals with experience in distributed training frameworks.
Experienced in building and fine-tuning large-scale vision and generative models with scalable production deployments.
Skilled in optimizing inference and training workflows using advanced techniques such as quantization, Flash Attention, and distributed GPU training (DDP, FSDP, DeepSpeed).
Proven technical leadership capabilities including leading design reviews, mentoring engineers, and collaborating across product and research functions.