AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and curate multimodal datasets
- Conduct end to end research and development of vision language models
- Contribute to open source AI ecosystems
- Design and implement knowledge distillation
- Design and implement reinforcement learning from human feedback
- Design and implement supervised fine-tuning
- Develop benchmarking systems and evaluation frameworks
- Develop distributed training workflows
- Implement model optimization compression and adaptation
- Monitor multimodal research and apply improvements
Perks/Benefits
Skills/Tech-stack
Benchmarking | Computer Vision | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Training | Human Feedback | Knowledge Distillation | Language Models | Learning from Human Feedback | Model Compression | Model Optimization | Multimodal AI | Parameter efficient fine-tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Vision Language Models | Vision-language
Education
Roles
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