AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain distributed training workflows
- Build and maintain multimodal datasets
- Collaborate on research publications
- Conduct end to end research and development for vision language models
- Contribute to open source AI ecosystems
- Design and implement post training methodologies
- Develop benchmarking systems and evaluation frameworks
- Improve model efficiency and scalability
- Monitor emerging multimodal research and apply improvements
Perks/Benefits
- Fully remote
- Global collaboration
- High autonomy
- Professional growth
- Publication support
- Work-life balance
Skills/Tech-stack
Benchmarking | Distributed Training | Efficient Fine Tuning | Evaluation Frameworks | Fine Tuning | GPU Computing | GitHub | Hugging Face | Human Feedback | Knowledge Distillation | Language Models | Learning from Human Feedback | Machine Learning | Machine Learning Pipelines | Model Compression | Model Optimization | Multimodal AI | Open Source | Open-source contributions | 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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