AI Research Engineer (Multi-Modal & Vision)
Tasks
- Build and maintain multimodal datasets
- Collaborate on research publications
- Conduct end to end research and development of vision language models
- Contribute to open source AI ecosystems
- Design and implement post training optimization methods
- Develop model evaluation and benchmarking frameworks
- Implement distributed training workflows on GPU infrastructure
- Optimize and compress models for deployment
- Translate emerging multimodal research into improvements
Perks/Benefits
Skills/Tech-stack
Benchmarking | Computer Vision | Data 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 | Open Source | Open-Source Development | Parameter efficient fine-tuning | Reinforcement Learning | Reinforcement Learning from Human Feedback | Source development | Supervised Fine Tuning | Vision Language Models | Vision-language
Education
Roles
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