AI Research Engineer (Multi-Modal & Vision)
Tasks
- Apply reinforcement learning from human feedback
- Build and maintain multimodal datasets
- Build and manage distributed training workflows
- Collaborate on research publications
- Conduct end to end vision language model research and development
- Contribute to open source AI ecosystems
- Design and implement supervised fine-tuning
- Develop model evaluation and benchmarking frameworks
- Implement knowledge distillation
- Improve model efficiency and scalability
- Monitor multimodal research advancements
- Optimize and compress models for deployment
Perks/Benefits
- Autonomy
- Flexible working arrangements
- Fully remote
- Open source collaboration
- Professional growth opportunities
- Publication support
Skills/Tech-stack
Benchmarking | Computer Vision | Data Pipelines | Deep learning | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Computing | GitHub | Hugging Face | Human Feedback | Knowledge Distillation | Language Models | Language Processing | Learning from Human Feedback | Machine Learning | Model Compression | Model Optimization | Natural Language | Natural Language Processing | Open Source | Parameter efficient fine-tuning | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Supervised Fine Tuning | Vision Language Models | Vision-language
Education
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