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Core Responsibilities:
- Conduct end-to-end research and development of vision-language models, including training, evaluation, optimization, and deployment.
- Design and implement advanced post-training methodologies such as supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
- Build and maintain distributed training workflows across GPU infrastructure while identifying and resolving performance bottlenecks.
Qualifications:
- Bachelor's degree in Computer Science, Machine Learning, AI, or related field; Master's or PhD preferred.
- Strong hands-on experience with multimodal AI systems, particularly vision-language models.
- Proven contributions to open-source multimodal AI projects through platforms such as GitHub or Hugging Face.
Benefits:
- Fully remote work environment with global collaboration opportunities.
- High degree of autonomy, ownership, and impact on product and research outcomes.
- Flexible working arrangements that support work-life balance.
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