2 дня назад
Senior Machine Learning Engineer (Generative AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Machine Learning Engineer (Generative AI): Improving the quality and performance of diffusion models for AI-powered fashion design with an accent on generative modeling, controllability, and applied research. Focus on experimenting with diffusion architectures, training and evaluating multimodal models on cloud GPUs, and translating prototypes into production-ready systems.
Location: Remote, United States
Company
develops AI design software that helps fashion brands and retailers analyze consumer demand and create designs using generative AI.
What you will do
- Conduct applied research and experimentation on state-of-the-art diffusion model architectures and training techniques.
- Implement and evaluate techniques that improve the quality and controllability of generated fashion designs.
- Analyze experimental results, draw conclusions, and communicate findings to technical and non-technical audiences.
- Collaborate with the ML team to translate research prototypes into production-ready systems.
- Track advancements in diffusion models, deep learning, and generative AI research.
Requirements
- Master's or Ph.D. in Computer Science, Machine Learning, or a related field, plus 3+ years of industry experience.
- Strong theoretical and practical understanding of deep learning and generative models, including GANs, VAEs, or diffusion models.
- Hands-on experience with deep learning frameworks such as PyTorch.
- Experience training and evaluating generative models on cloud GPU platforms such as AWS, GCP, or Azure.
- Proficiency in tuning multimodal LLMs through both API-based and open-source implementations.
- Ability to present complex technical information to technical and non-technical audiences.
Culture & Benefits
- Full-time remote work from the United States.
- Opportunity to work on generative AI applications for the fashion industry.
- Research-focused collaboration within a growing machine learning team.
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