AI Research Engineer (Multi-Modal & Vision)
Tasks
- Apply knowledge distillation
- Apply reinforcement learning from human feedback
- Build benchmarking systems
- Build multimodal datasets
- Conduct end to end research and development of vision language models
- Deploy AI models
- Design supervised fine tuning
- Develop model evaluation frameworks
- Implement distributed training workflows
- Optimize model efficiency and scalability
Perks/Benefits
- Fully remote
- High autonomy
- Professional growth opportunities
- Research publication support
- Work-life balance
Skills/Tech-stack
Benchmarking | Computer Vision | Dataset curation | Deep learning | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Computing | Human Feedback | Knowledge Distillation | Language Models | Language Processing | Learning from Human Feedback | Machine Learning | Model Compression | Model Optimization | Multimodal Learning | Natural Language | Natural Language Processing | 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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