AI Research Engineer (Multi-Modal & Vision)
Tasks
- Apply reinforcement learning from human feedback
- Build and maintain multimodal datasets
- Conduct vision language model research and development
- Contribute to open source AI ecosystems
- Design and implement supervised fine-tuning
- Develop distributed training workflows
- Develop model evaluation frameworks
- Monitor performance bottlenecks in training
- Optimize and compress models for deployment
- Perform knowledge distillation
- Translate research advances into practical improvements
Perks/Benefits
- Flexible working arrangements
- Fully remote
- High autonomy
- Professional growth opportunities
- Publication support
Skills/Tech-stack
Benchmarking | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Training | GitHub | Hugging Face | Human Feedback | Knowledge Distillation | Language Models | Learning from Human Feedback | Machine Learning | Machine Learning Pipelines | Model Compression | Model Optimization | Multimodal Learning | Open Source | Parameter efficient fine-tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Vision Language Models | Vision-language
Education
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